CEOInterviews.AISiemens | Live from Hannover Messe 2026

U

Unknown0:23

Hey. Hey. Hey. Heat. Heat. N. Heat. Hey, heat. Hey, heat. Hey, hey, hey. Let's go. Hey. Hey. Hey. The rain. Grab that. Hey. Hey. Hey. Heat. Heat. Heat. Heat. Heat. Hey. Hey. Heat. Heat. Feel the best. Hey, hey, hey.

A

Announcer11:12

A wonderful good morning ladies and gentlemen. This is day five live from Hanover Mass Hall 27, the living room of innovation. Max and Christine are back.

C

Christine11:24

Good morning. And Christine's already taken her shoes off and I'm glad you took yours off and not me because otherwise everyone in here would need a gas mask.

M

Max11:31

We wouldn't have had visitors at our booth for the whole day if it was you.

C

Christine11:35

So, as a matter of fact, I'll do that now. What goes to most favorite in their daily activities? Think of new shoes. And as a matter of fact, we have this analysis tool here at our fair booth. And now I will unveil to the world that I have a flat foot on my left side. Thanks, Dad. I'm a platform Indiana on the left. Max, what would your foot sole look like?

M

Max12:04

Um, I think it just be red everywhere.

C

Christine12:08

Yeah, you got the hot feet. Now I have Joseph Flynn, one of our colleagues who has been working hard and heavily here making girls happy with new shoe soles. Flynn, uh, Joseph, what are we doing here? What are we actually providing?

J

Joseph Flynn12:23

So, we're showing that when you have lots of products and each of them are unique, we can still manufacture those efficiently. We're telling that story with shoes here today. And what we can do is take the data from the pressure sensor and we use that to change things about the areas of this sole. Some will be softer for cushioning, some will be harder for support. And each one is unique to the person who steps on the sensor.

C

Christine12:50

So we will get a very very unique sole for me very very soft and make data work for you. This is the motto of this year's fair. You still have six hours to come to Hanover. So give it a go or you watch the recordings of our presentations from the previous days where we unveil what we have to show in regards of technology and innovation. Max, what's on schedule today?

M

Max13:17

Well, we have Miki coming up in just a second, our running reporter. He's got another session today. I'll be on stage in a talk about the ERA initiative cloud edge. Quite exciting for Europe especially. So, I'll be hosting that and we have a special thing for partner country as well later on, but I'm not going to give it away. Brazil is this year's partner country and we had great presentations. We had great customer success stories on stage already. So don't miss that one. That's going to be five to 12. That's what we're going to unveil. Who's next year's partner country and what the recommendation of this year's partner country Brazil is to those who have the honor to jump in next year in regards of customer storytelling and bringing a large delegation to our fair booth?

C

Christine14:06

Exactly. Should I go and make my way around the booth quickly and then hand over to Miki while you...

M

Max14:11

I'll optimize my shoe printed and then I'll have a soft and easy day at the fair with perfectly fitted shoe soles.

C

Christine14:20

And then you'll get some nice blue shoes like our colleague over there. They do look exciting. We still have to get our hands on them. The hardest thing to get here. I'm going to throw my flitter boots away and I'm going to go for the perfectly individualized super cushioned shoes.

M

Max14:43

All right, we will see you later and we're going to take a short walk. This is our innovation hub. We are showing what the future of industry might look like here. Everything is going to be orchestrated by AI: entire designs, operation workflows, the whole thing for more autonomy and more flexibility. We have the shoe sole example here in the center. We have physical AI with robots and AGVs that can think and act autonomously. On the far side, that is our digital enterprise for consumer packaged goods, an end-to-end showcase showing how core technologies can help from design to the supermarket shelf. We have three exciting customer examples: Pringles, Natura, and PepsiCo. Over here is our technology deep dive with four customer islands: advanced machine engineering, smart manufacturing, electrification and buildings, and systems engineering. We have various highlights like ECGPD for switching and protecting, serious controls, industrial controls. Also integrated into the booth are our partners because we believe a collaborative approach is the only way to achieve true digital transformation. And with that, I'm going to hand it over now to our running reporter Miki.

M

Miki17:20

Thank you very much Max and welcome to our last day here at Hanover. Next to me is Gamza and she's a marketing manager here at Siemens and together we are standing on a LED glass floor, right? And I want to know we have a lot of products here. What exactly are we seeing?

G

Gamza17:40

Good morning, Michael. Here at our exhibit, we are showcasing three new product innovations with a groundbreaking technology. The first one is our Centron ECBD, an electronic circuit protection device, now a three-phase version. The second is a SIRIUS ET200 SP starter for fully electronic motor starting with safety functions. The third is a semiconductor circuit breaker, the Centron 3QD2 for DC power distribution.

M

Miki18:23

That sounds big. What are these innovations and what makes the technology special?

G

Gamza18:27

We combine semiconductors, microcontrollers, and intelligent algorithms to ensure super fast switching. These devices are up to 1,000 times faster than conventional devices and are super fast for short circuit protection. This is important for DC applications. There are three main reasons: DC short circuits rise extremely fast, DC has no zero crossing, and electronic loads are extremely sensitive to voltage drops. To wrap up, we have these three new innovations with semiconductor technology. If you want to learn more, come to our booth.

M

Miki19:54

All right. So you've been here a couple of days as well. What's been your favorite and your impressions about the fair so far?

G

Gamza20:02

It's really full. It's busy. We had great talks with our customers. It's really nice to be at such a fair to get the feedback from our customers live.

M

Miki20:18

We now head back to the stage. Thank you very much and back to the stage.

C

Christine20:34

Thank you Miki. Thank you Gam. Great way to kick things off here. Now, up next here on the stage on our LED in the stream, we want to show you some highlights from day one when the chancellor of Germany came to our booth. So, please enjoy the show.

N

Narrator21:04

A video montage showing highlights from the fair, including the chancellor's visit, scenes from Brazil, and glimpses of the exhibits.

M

Miki28:23

I'm on the floor here and I'm joined by Salma Khn, head of marketing for sustainable services at Siemens. Hi Salma, it's great to have you here at Hanover. So I'm going to dive straight in. When we talk about industrial business today, sustainability plays a huge role. What are you showing here under industrial sustainability services?

S

Salma Khn28:31

Hi, it's great to be here as well. For me, sustainability services help our industrial customers to stay resilient and competitive over long term. We enable them to use existing resources more efficiently, extend lifetime of assets, and reduce operating cost. Today we show three key offerings: circularity with circular repairs and spare services, retrofit and modernization services, and energy efficiency services. The exhibit behind me shows energy efficiency in action.

M

Miki29:28

Amazing. It sounds really interesting. I've already had the chance to look at the circular repair services. Can you tell us a little bit more about how these services work in practice?

S

Salma Khn29:38

Let me start with circularity. The demand for natural resources is getting less, so we need to change from linear to circular economy. We help customers with refurbished and remanufactured automation products, extending lifetime with high quality and fast delivery. Retrofit and modernization upgrade automation and control systems, improving productivity while saving initial investments. Energy efficiency services provide data-driven transparency into energy resources, helping identify improvement potential, reduce carbon emissions, eliminate energy waste, and reduce operating cost while staying compliant. Examples include DCS modernization for Munich wastewater management and urban waste management in Portugal, and a steel industry customer Sitenor in Greece saved 46% more energy after an energy audit.

M

Miki32:46

Yeah, if you're not sold already, I don't know what else will. Highly encourage everyone to come to 183 where you can learn about the sustainability services we have to offer. I think I'm going to hand it back to the gallery studio now. Thank you, Salma.

S

Salma Khn33:05

Thank you.

S

Studio Host33:19

I've got Dr. Matias Opel from Siemens. He will show us what's happening today in the world out there and live. Let's move on to you. Good morning.

M

Matias Opel33:28

Good morning. Thank you for having me and it's a real pleasure to be this year at Hanover again to talk about how dreams become reality. Looking at autonomous production and industrial AI, it's fascinating. AI is almost everywhere. I'm Matias Opel and I have the privilege to lead many years to help people, organizations, and technology come to their full potential. In industrial contexts, we face headwinds: scarcity of resources, fragility in supply chains, shortage of labor. We need to be adaptable, flexible, fast, and resilient. Siemens has its own factories, like the lighthouse factory in Langan, which has the ambition to become the first AI powered autonomous factory. We drink our own champagne. To master the transformation, we need industrial AI, not just general AI. Industrial AI must be rock solid, safe, reliable. We need an industrial foundation model that understands engineering languages and modalities. We also need IT and OT convergence, software-defined automation, and collaboration. Our vision is to build an open ecosystem, partnering with companies like Nvidia and startups, via the Siemens Xcelerator platform. Data is key. We need to turn data into valuable insights. The most important moment is now. Let's shape the future together.

S

Studio Host48:15

Thank you. I like the together. What makes that so important? What changes it for us?

M

Matias Opel48:24

What makes it so important is that the challenges we are all facing are so strong that nobody has the 100% answer. We need data centers, AI models, compute power, but also industrial domain expertise. No single company has it all. If we combine our strengths, we can build a better future together.

S

Studio Host49:03

That's really cool. I took away from our discussion with partners that you know that was the point. It was really talking to your customers about what's working, what's not. Do you have an example with one of your customers where this is really working and flowing for you?

M

Matias Opel49:39

The example is our own factory in Langan. We walk the shop floor, identify where the highest potential is for increasing autonomy and productivity. We are also discussing this with many customers. It's not an office conversation; we go down on the shop floor, combine IT and OT, identify use cases, and implement against the biggest problems or potentials.

S

Studio Host50:21

This is what we need. I remember walking through the gateway, it felt like stepping into a portal. That alone was impressive. What has changed the most in the last 5 years from your perspective?

M

Matias Opel51:18

The most change is the people, the mindset, the openness to adapt new technology. When we explore humanoid technology in the shop floor, workers are interested and say they would welcome help. The mindset of exploring what becomes possible and moving the envelope further out with our technology and expertise. In the AI space, the last five months or weeks have been fascinating with rapid model evolution.

S

Studio Host52:14

If we look at the next 5 years, what do we really need to do to move the needle? What needs to be done Monday morning?

M

Matias Opel52:45

Start sharing data. Data is important to train models on industrial grade, to understand further use cases, and enrich the validity of models. It starts with the first step and leaning in on data. We all sit on our data pots, but we need to share to realize the full potential.

S

Studio Host53:13

I love that sharing is caring. I had a great chat with you. This was very spontaneous and that's the moments we love. Matias, great having you here. Thanks for being with us.

M

Matias Opel53:33

Thank you.

S

Studio Host53:48

With me is Miriam, one of our tour guides, and she can tell you more about what you can see in the electrification and buildings area. Miriam, thank you very much. I will hand over to you.

M

Miriam54:07

Okay. Thank you. Also a warm welcome from my side. My name is Miriam. I'm a business developer and during fair time I work as a tour guide. Our electrical infrastructure is under pressure. Electrification and digitalization are accelerating while we face aging assets. I'll take you on a tour. We have medium voltage switchgear, blue GIS, NX plus C, F-gas free. We have Zroek relay for monitoring and protection, and Zprotect Wii virtualized protection server. Next, the 8DJH 24 secondary distribution switchgear, smart with C bushing collecting current and voltage values. Data is collected and used in a digital monitoring system. Electrification X dashboard shows contextualized data from a solar power plant. Finally, the Sivacon low voltage switchboard with withdrawable functions, smart motor control, busbar trunking system for flexibility, and arc fault detection. I invite you to come to Hanover and check out our DC solution.

P

Presenter1:00:01

So, I'm just going to say 90%. We spend 90% of our human life in buildings. Buildings are the spaces where we live, learn, work, and heal. They are a huge lever for energy savings and reducing carbon emissions. 40% of all energy is used by buildings, and 75% of EU buildings are not energy efficient. By 2050, the world population will be 9.7 billion, with 68% in urban areas. Every building needs to operate more efficiently. Our technology enables the path from smart to human centric autonomous buildings. Autonomous buildings are intelligent and self-optimizing, powered by AI and integrated systems. They learn, prescript, and act with minimal human intervention. Performance: daily operations are self-managed, issues identified before they occur. Energy savings: data-driven systems optimize complex energy flows across assets, grids, environments. Safety and security: fire safety systems self-test, security systems recognize authorized individuals. Flexibility: spaces and operations adapt. AI is used for pattern recognition and forecasting. Digital agents orchestrate responses across building systems. I'll show you our AI-based HVAC closed loop optimization live at the booth. It combines real-time sensor data, weather forecasts, and thermal building models to calculate optimal heating and cooling in advance. Also, energy load optimization reduces overall energy costs by 15% by automatically reducing peaks and shifting loads with AI, reacting to price signals and forecasts. This results in lower energy spend, CO2 reduction, and stabilized operations. To learn more, visit our booth.

Now let's also talk about our energy load optimization live at the show here. We can show you how to reduce overall energy costs by 15% thanks to our energy load optimization. Energy costs are rising due to grid fees, volatile prices, and electrification pressure. Operations struggle to react fast enough. Renewables and electric loads increase fluctuation. Manual energy operations leave flexibility unused. With energy load optimization, we automatically reduce peaks and shift loads across the building with AI optimization, reacting in real time to price signals and forecasted data. This results in lower energy spend, cutting CO2 emissions, and stabilized operations. Our customer can flexibly manage energy demand and collaborate with the grid. If you want to learn more about human centric autonomous buildings, visit us at Hanover Messe at the booth. You can also find the Building X system on our Siemens Xcelerator platform.

M

Miki1:09:07

Thank you. Welcome back to the floor. I'm joined by Christina Mersburgger, marketing manager for sustainable services. So, welcome Christina. We're here at the Siemens booth to talk about circular repair services and how shifting to a circular economy is no longer a nice to have, but a catalyst for business growth. Why is it important to shift to this circular economy?

C

Christine1:09:45

Yes, thank you very much. Where the linear economy was based on the model of take, make and waste and this has served us now for more than 40 years but it's reaching its limits now. So we can see that with resources, supply chain disruptions and with the global volatility that it's really important to do more with less resources and shifting to a circular economy is not just a nice to have anymore for our customers. It's really a business opportunity.

M

Miki1:10:16

Great. And one business opportunity is circular repair services. What are they about?

C

Christine1:10:21

Yes. So if we take a look at our exhibit here, you can see what it looks like when we get products back from our customers. So take for example the simatic HMI panel or sinamics. So you can see the scratches, you can see that they're nonfunctioning anymore, that they are dirty. And then with the Siemens magic, our customers with circular repair premium, they get it back in a condition that is as new in performance and appearance. So this is the remanufacturing from Siemens. And what's also really great is that our customers benefit from the high quality of the original manufacturer. And this is why we also give our customers a warranty of 24 months. And there is also circular repair advance. This is the second option of our offering and this is basically about putting it back to full performance but with a more cost effective way. So also at the very high quality.

M

Miki1:11:23

Wow. Okay. I mean it's such a great concept to bring back your products and revamp them so we're not wasting. How do our customers benefit from these services and why should they buy only from Siemens?

C

Christine1:11:36

Yes. So they benefit basically because they extend the lifetime of their products and their machines. And they also increase their planned availability thanks to our global network of more than 160 repair centers. And what's also very best is that they save resources and costs because they shift their investments to operational expenses. And this is how they stay competitive and also gain a huge business advantage. And why should they buy from Siemens? I mean the answer is pretty clear because who could you trust more than the people who originally built the products. So you get the highest possible quality from our service experts when it comes to testing, when it comes to updates. And what's also best is that we ensure that the products come back in compliance with safety and industry standards. So, if you would like to find out more, please visit us here on the fairground at station 120 or tune in later at 1:50 p.m. when we talk with our customers, spare parts now, how we can take circularity to the next level.

M

Miki1:12:47

Yeah, brilliant. You've summed it up really well there. So, we've got a brilliant concept and a really useful thing for all of our customers. So, as Christina said, get yourself down here if you'd like to learn a little bit more or tune into the talk later on. And with that, we're gonna hand it back to the gallery studio. Thanks, Christina.

C

Christine1:13:07

Thank you very much.

M

Miki1:13:22

Hi. So we are at the CPG area here with showcases and our cooperations with our partners like PepsiCo, like Pringles and Nura and many more. We have to keep it a little bit short, but Tyler, you are an industry development lead for CPG and you will tell us which role all of our products have in the industrial metaverse that Siemens is promoting and pushing and what it does to help our customers. Tell us, please.

T

Tyler1:13:53

Yeah. So, full transparency, I used to think of the industrial metaverse initially as a photorealistic environment to take pretty pictures. I then evolved my thinking to be a bit more of a collaborative engineering environment. And now I think I've really figured out it's a multifaceted collaboration environment. Yes, you typically start making engineering decisions, gaining quick consensus, doing virtual validation and commissioning, making sure that lines and optimizations are going to be appropriate, but it has such a long life cycle associated with it where you can get into maintenance planning, operator training, safety training, closing the loop and democratizing models.

M

Miki1:14:28

So digital twins do also play a role in that. Can you please explain a little bit what they do?

T

Tyler1:14:34

Yeah, that's a great question. So, actually last week I was working on a presentation for a customer and they came to me and said, 'Please do not talk with us about how to build a digital twin. We get it. We have to make decisions on how we're going to move forward with that.' And I looked at them and I said, 'Has anybody really talked with you about how to use a digital twin?' And they kind of perked up and got excited about that. So, that's a story that I've been relaying here both with our internal leadership and with customers and it seems to be resonating quite well. We talk a lot about building these models and constructing them appropriately, but how do you actually utilize them? How do you create a closed loop system to make these engineering decisions? And that's where the digital twin really comes into play.

M

Miki1:15:14

All right, one last question also regarding the industrial metaverse. How is Siemens supporting making it real? What are we doing there?

T

Tyler1:15:22

So, first and foremost, we're working with key partners and key customers to really bring this to life, right? So through the PepsiCo product project, we birthed the new product that was announced at CES in January, the digital twin composer. So that's one example of how we're making it easier to go from this industrial foundation of these different 3D models and geometries into the industrial metaverse, building these global scenes, making it much easier for customers to take that leap and move forward.

M

Miki1:15:50

All right, thank you very much for the insights. If you want to learn more about what we are doing with PepsiCo here and our other customers, head over to the CPG area, talk to our colleagues like Tyler and learn more. Thank you.

N

Narrator1:16:08

How can CPG companies turn data into value and accelerate the journey from idea to consumer with maximum efficiency? Our digital enterprise expert will explain. The digital enterprise combines industrial software and automation to create a seamless data flow from design to optimize. With a digital twin, data fabric, and industrial AI, companies can achieve faster, more sustainable product design and production. Examples: Pringles used industrial AI to boost capacity by 10% without new lines. Nua reduced water and energy consumption by up to 50% with digital twin technology. PepsiCo identified 90% of issues before implementation and achieved 20% higher throughput. Siemens is leading the industrial AI revolution, providing AI built for the real world. The time to act is now. Thank you.

M

Miki1:36:15

Thank you very much for the very tangible examples. It's not just a theory behind it, but you also showed us where we help our customers. But you also brought something else with you. Those cups, I've seen them. What are they? And how do I get one? Now, these cups are something that you can win. If you go right over there or you see it also on the screen where the digital enterprise for consumer packaged goods showcase is. If you go there, talk to our experts, get through the entire end-to-end story, you can collect some stickers and win this coffee mug. So go ahead, enjoy your time, talk to our experts, and have a good coffee time later.

Thank you very much. And that's a very good reason to go over there. Now I hand over to Max and he's going to tell us what's up next.

M

Max1:37:08

Thanks very much, Mickey. Great job. So, welcome to Hall 27 everybody. In case you have not yet taken a seat on our excellent stage area here, then please do so. We have many free seats for you. There's no need to stand around at the back. Come closer. We have a great talk lined up for you next. So grab a seat and enjoy the show because next up we are going to be talking about the global challenges and long-term vision of the European cloud edge initiative called Aura and our guests will share their views on the anticipated demands and expected benefits. So please welcome with me here on stage from SAP Thomas Klingbal and from Siemens Sirinel. Welcome gentlemen.

Hi. Take a seat.

T

Thomas Klingbal1:38:06

Thank you for inviting me.

S

Sirinel1:38:06

Hi. Thanks for having us. Take a seat.

M

Max1:38:10

So, gentlemen, the final day of handover. Thank you so much for joining us here on stage. Um, Thomas, you are the director of innovation enablement at SAP and Sir, you're a principal key expert for edge and cloud computing. I would like to briefly explain the Aura initiative: it drives the development of a sovereign, interoperable, secure multi-provider cloud edge continuum, with over 120 partners from 12 EU member states. It fosters open collaboration for a resilient digital infrastructure. And now, Thomas, can you explain the main challenge you wanted to address with Aura?

T

Thomas Klingbal1:39:52

Yeah, the biggest challenge in cloud computing is the plethora of possibilities, but you have to adapt your software for each platform. Scaling across multiple providers is complicated. SAP has always aimed to support multiple providers, and Aura provides a reference architecture that enables workloads to run on any infrastructure and scale across them, making the cloud work better.

M

Max1:40:50

Sir, how about you? What was your motivation to join?

S

Sirinel1:40:52

We see the same situation on the industrial operation side: a plethora of non-interoperable edge platforms with high vendor lock-in. When we saw the ambition on the multicloud side, it matched our vision of industrial edge computing. We wanted to bring Siemens' expertise to make a multicloud edge continuum.

M

Max1:41:42

Now, we've spoken about security concerns. Aura is open source. How does that contribute to digital sovereignty and security?

T

Thomas Klingbal1:42:15

Open source means the software is free and anyone can review the source code, make changes, and ensure compliance. There are no hidden parts. It's future-proof because no single company has full governance, and you can continue using it. It even enables smaller contributors to participate, benefiting from distributed development.

M

Max1:43:16

I see you nodding. Do you agree?

S

Sirinel1:43:18

Yes, it's a perfect match. Customers want to avoid vendor lock-in. Open source creates trust and allows them to continue their business even if a vendor disappears. The same principles that create trust and sovereignty in the cloud apply to the edge.

M

Max1:44:03

Now you mentioned vendor lock-in. What strategies ensure interoperability?

S

Sirinel1:44:19

We have to accept many vendors providing edge technology. Common standards and federation mechanisms allow interoperability. For example, identity access management must be agreed. These strategies, including federation, make the setup future-proof.

M

Max1:45:27

Let's move to practical use cases. How do you contribute to smart production?

T

Thomas Klingbal1:45:39

We've been contributing to Kubernetes and cloud workloads with Gardener to orchestrate workloads, and Garden Linux for bare metal. The data fabric ensures data flows from production to data centers, and the ability to shift workloads closer to data sources depending on requirements like sustainability.

M

Max1:46:44

Sir, what about you? Any progress?

S

Sirinel1:46:46

Yes, we recently concluded a proof of concept showing that the multicloud approach from SAP can extend the edge to create a real edge-to-cloud continuum. For example, in machinery-as-a-service, an OEM can now choose different edge and cloud providers, gaining resilience based on the foundations of the Aura initiative.

M

Max1:48:18

I'd like to shift to market opportunities. How will edge computing and AI evolve over the next 5 to 10 years, and how will initiatives like Aura benefit the market?

S

Sirinel1:48:22

The vision is to extend the cloud-edge continuum to AI, lowering the burden for scale in OT-IT convergence. This will boost use cases, more edge platforms, and edge-to-cloud. New business models like subscription services will become feasible, and AI will act as an accelerator, forcing us to do the homework to make AI scalable in the next one or two years.

M

Max1:49:16

Do you agree, Thomas?

T

Thomas Klingbal1:49:18

I agree. AI will change how we process data. It will become more important to process data closer to where it is needed to avoid transporting huge amounts, using open software stacks.

M

Max1:50:01

Sir, how will the manufacturing market develop as a result of Aura?

S

Sirinel1:50:07

Use cases that are not feasible today will become feasible. For example, everything related to subscription models requires reliable edge-to-cloud communication. AI shows the bottlenecks we have, and we must now do in one or two years what we've tried for 10 years to not lose track. We need to enable customers.

M

Max1:51:29

What are the next steps for Aura?

S

Sirinel1:51:34

We have achieved a reference architecture that will be finalized in the coming months. Two foundations, NEON and SILVA, channel the software for telecom. It's all about adoption and scale, creating a developer community. The project will be extended with a 2.5 billion euro funding for AI at edge. If interested, visit us in hall 13.

M

Max1:53:03

How long are you going to be there today? It's the final day.

S

Sirinel1:53:07

Until end of day.

M

Max1:53:10

Me too. Ladies and gentlemen, make the most of that opportunity to speak with Sir and Thomas. We look forward to seeing you again. Thanks, Sir and Thomas. A round of applause, please. Thanks again.

Enjoy the rest of the day here in Hanover. See you soon.

And with that, we're now going to catch up with another one of our experts who's been in an interview with our running reporter, Izzy. Over to you.

I

Izzy1:54:09

You've joined me at the accelerated product development station. We're going to dive into VR headsets and see how digital twin technology can help build something like this plane. Let's move over to Mario Desperara, a technical account manager at Siemens, who's virtually building a plane. Hi, Mario.

M

Mario Desperara1:54:35

Hi.

I

Izzy1:54:37

First question: what is this VR headset used for?

M

Mario Desperara1:54:46

The main focus is collaboration. For example, with a large ship, you can put on a VR headset and review it from anywhere. You can take measurements, do design collaboration, and see photorealistic textures. It's useful for marketing and engineering, allowing real-time design changes.

I

Izzy1:56:30

So it sounds like you can build anything anywhere. What is the most special thing about this tech?

M

Mario Desperara1:57:21

Because you feel it. With a model, you can sit inside and see how reachable things are. It's like being in a video game. That's special.

I

Izzy1:57:56

Great. Thank you, Mario. So we're going to move over to a drone. I'm joined by working student Yanick and PhD student Jerry Schul. Hi guys. How are you?

J

Jerry Schul1:58:12

Yeah, very good. So what are we looking at here? What's it used for?

I

Izzy1:58:22

So we are seeing here a drone. It's a rescue drone developed in collaboration with the Austrian mountain rescue team. It's intended for injured hikers, enabling quick and efficient rescue. I'll move over to Yanick. Can you tell us what is special about the drone?

Y

Yanick1:58:54

What's special is not only what it does, but how it was developed. It was developed in our research center at the Technical University of Graz. We integrated many Siemens software products in one room to show the power of the portfolio. For example, an overheating issue was identified and the drone was redesigned within a week.

I

Izzy1:59:48

That's fascinating. You and Jerry are students. How does it feel to be here at Hanover Messe and see the real world?

Y

Yanick2:00:03

It's an honor. I work for Siemens DISW for about two and a half years. It's amazing to bring our knowledge to customers and talk about real problems.

I

Izzy2:00:24

Brilliant. Thanks so much guys. Okay, with that we're going to move over to the mighty innovation hub.

P

Presenter0:37

You can see the hustle and bustle. We can't get through. We're trying.

There we go.

Excuse me. Sorry. Still with me.

Velia, would you mind joining us for a quick chat?

V

Velia1:16

Hi. So,

P

Presenter1:18

Great. So, we're here at the innovation hub and I'd love you to tell us about the sensory development of the robotics at Heirlang and factory.

V

Velia1:26

Yeah, for sure. So, obviously we can see here kind of an end-to-end innovation showcase, right, of a highly flexible adaptive production. And I come from our own Siemens's own electronics factory in Alangan. And one of the challenges that we have is that we have a lot of different products that we need to manufacture and we kind of have low to mid volume. So we don't have a lot of a certain product that we can manufacture. So traditional automation doesn't really work for us because it's just too expensive a lot of the time. So cases like these that bring intelligence actually down to the hardware that helps us be more flexible and adaptive is exactly what we need to continue making our factory more productive. And this is kind of an application use case for physical AI where robotics start to learn doing their own task and obviously this is also a lot of part of the future outlook of where robotics are headed. But in our factory also started a couple of years ago even bringing intelligence into the robots. We started teaching them how to feel for example where they had like very fuzzy assembly tasks that they needed to complete without damaging the product. We had also the cases where we needed to teach our robots how to see, identify different parts that needed to be picked up and put into package for example using semantic pack pick-and-place also. And now obviously we're excited for the next step also with partners like Nvidia to see how we can bring more and more flexibility and intelligence down to the robotics level.

P

Presenter2:55

Yeah. Amazing. So we can see how reactive the robot arm is here. What would you say is the most special thing about getting to work with kind of at the forefront of this tech and yeah, what's exciting about it for you?

V

Velia3:10

I think the excitement mainly comes from not being in the lab environment but having a process that needs to adapt that new technology right for our real production. There's real customers waiting on our products. So this shift I think is really special from in theory it's possible or in a lab it's possible to then actually translate it into real production environment and have that proof point that we can also demonstrate to customers that it works reliable in a process. So that is a cool interface between those two worlds, innovation, but then when it hits reality, what do you need to do to make it work?

P

Presenter3:49

Yeah. Okay. And with this technology, what would you say was kind of the biggest challenge to getting it to where it is now? Is that obvious for you?

V

Velia3:58

I mean the colleagues obviously are doing an amazing amazing job and a lot of the research partners are on the forefront of that technology development but you do need to give it a reality check sometimes and you need to talk about the complete systems life runtime life cycle management service. So all of this is kind of the maybe the unsexy bit that still needs to be talked about and figured out. Yeah.

P

Presenter4:25

Yeah. Right. Okay. And so in the factories, obviously we're not making trainers as we can see here today, but it's more hardware technology.

Okay, cool. And when you've had people visiting you today, has there been any questions that have kept rising up? Have you had similar questions?

V

Velia4:46

Well, so far we're pretty much in the beginning of the fair. So not a lot of repeat offenders, let's say. But I think it's cool for us as a factory to be here represented on the fair, right? Because we serve as our own kind of proof point. So people don't expect to be talking with factory people and then they kind of perk up when they realize, oh, you're doing it or you're actually using it. So that's always amazing coming here.

P

Presenter5:10

Okay, brilliant. So I think are we almost at time? Two minutes. Well, should we have a little walk around and see what else we can find in the innovation hub? Let's follow. Let's have a look.

So, as you can see, the robots that Via was talking about, we can see them in action here. And it's so amazing to see how adaptable they are and how quick they react to what's around them. Let's see if we can get a good shot here. Okay. Wow. So, you've seen it here live in action. You've got a POV of the innovation hub and I hope you've enjoyed our chats with our guests today. I'm going to throw it back to Max in the gallery studio.

In the age of AI, energy is getting more important. But what is also more important is sustainability and merging those two topics. We are here at the Siemens booth looking at our Ecotech sustainable control cabinets and next to me are Vira and Johan and they will be telling us much more about what you can see here. So my first question goes to you Vira. What is this cabinet and what is so special about it?

V

Vira7:10

Hi. So this cabinet is a strong example of how Siemens walks the talk when it comes to sustainability and also demonstrating how products with the Siemens Ecotech framework help reduce the customers' carbon footprint overall efficiency and so on. And what is so special about this cabinet is that this is the world's first cabinet produced with sustainably produced steel. And what this means is that there is a massive reduction of 70% carbon dioxide with the help of this cabinet. So which means that around 300 kilograms of CO2 saved per cabinet. And it's not only about the cabinet, it's also about the products inside. So these products are designed with the eco-design framework which means they are energy efficient, low carbon footprint and produced from sustainably sourced materials. Yeah. So this is an example.

P

Presenter8:16

Okay. My next question goes to you Johan. Can you give us a concrete example of a product from the Siemens Ecotech framework within the cabinet?

J

Johan8:26

Yeah, sure. Maybe you have also seen yesterday's panel presentation about our Ecotech framework and just like Vira also mentioned it's about 13 eco-design criteria and we improve a lot of them in order to make our products more sustainable. And my example is here a S7 1500 CPU. I have here an old version and a newer version. You don't really see the difference but you feel it in the weight because taking the example of minimum material use, we were able to reduce the plastics, we were able to reduce the amount of metals and also make the PCB smaller. So in the end, depending on the variant of the CPU, 14 to 45% less weight compared to the previous product. And less weight, less material means then also less CO2 footprint for our customers.

P

Presenter9:14

All right, this sounds like a huge development and change to what we had in the past. Vira, what are the benefits of a product within the Siemens Ecotech profile framework for our customers besides what we already heard?

V

Vira9:27

Yeah. So that's a great question. So first of all, sustainability is making business sense. Yeah. So the first benefit is that it really boils down to the cost because by using products with the Siemens Ecotech framework, it's not about only the costs which are reduced at the initial purchase but it's also during the lifetime because these products are more energy efficient, less carbon dioxide used and produced with more sustainable materials. Second is the topic of reputation. So by using products with the Siemens Ecotech framework, you are also giving a positive impact to your customers and partners and setting an example of how you are serious about the environmental footprint. So this is also a great example. And third but not least is that you know that the regulations are getting stricter day by day. So by using products with the Siemens Ecotech framework, you are also getting closer to your goals. So this is also a big huge benefit. And most important is by using Siemens Ecotech products with the framework, you're getting the same quality and durability as what is popular for Siemens. So this is also the big highlight with us. Yeah.

P

Presenter10:48

All right then, one of our last questions. Will it be available on the booth and where can we find more sustainable information about Siemens products?

V

Vira11:02

What also is important for me to say is that you will find sustainability and sustainability offerings from Siemens not just in our booth but everywhere around. We have services around energy efficiency when you take the Energy Manager Pro. You have services around making production more efficient, make your products more efficient. Taking the example of the Siemens digital twin, also services offerings for decarbonization, helping our customers to decarbonize. Why I say this? It's important to know that sustainability is really on the heart of a lot we are doing. But if you really want to see our products, how we make them more sustainable, then come to our booth 180 and 175. They're just here close to each other. Let's talk about our cabinet and let's talk about our concrete products. Yeah, see some examples of how we make sustainability happen.

P

Presenter11:54

Okay, so you mentioned both exhibits here. What is the difference between 175 and 180?

J

Johan12:02

So on the one we have the cabinet like Vira mentioned, it's possible for our customers to order a whole cabinet with CO2 reduced steel with Siemens Ecotech product inside. At the other booth we show concretely on the ecolabel what is the framework, what are the concrete eco-design criteria we're improving. So we could look at distinct products, look into the Siemens ecolabel profiles and see the sustainability of our products itself.

P

Presenter12:31

All right. So if you have one thing to take away for our visitors here, what would you say is that?

V

Vira12:38

So as you know what the situation is happening around the globe, AI definitely is the hot topic but it's also important to also catch up on the regulation sustainability because things will also change in the future. So it's always good to start preparing for this journey right away. So with products from Siemens Ecotech framework, you are rest assured that you are way ahead of this journey. So I would ask our customers to visit here and also get some more information about the products.

M

Max13:22

We are going to discover next how Siemens and AWS are accelerating industrial AI at scale using real-world vision AI deployments in the Siemens electronics plant in Langen. And by standardizing this joint Siemens industrial edge and AWS architecture, deployment times have been able to drop from months all the way down to days. And here to tell us more, I'm glad to be joined now by our two guests -- from Siemens, advanced optical inspection and closed loop manufacturing expert Marvin Herbach, and from AWS, principal partner development manager for industrial Dr. Henning Hudov. Gentlemen, thanks for being here. The stage is all yours.

H

Henning Hudov14:13

Perfect. Thank you very much, Max, for the warm introduction. We are very happy to be here for this presentation. And before we go into the details of the great things that we've been doing together in the electronics factory in Alangan, let me tell you a little bit about the origin, the history of our partnership which originated roughly around 2015. And for those of you who remember 2015, 11 years ago, that was the year where Apple brought out the new Apple Watch. 1 million devices sold within the first 6 hours and ambiguous computing was everywhere. People got connected. Here at Hannover, it was the beginning of industrial 4.0. The promise of connected devices bringing productivity gains. Siemens of course, Marvin was already here. AWS was not yet here on the stage. We waited for another two years until we released our first product actually together with Siemens. And what we already started building out there is what you see on this presentation, bringing together AWS and Siemens. Siemens mostly comes with the deep history of hardware in the field. What you see on the slide in the lower left corner is the connectivity, the data integration and this cannot be overexaggerated. It's crucial that you as an end customer and also a machine provider have access to the data and typically it's a lot of brownfield. So you need to have the knowledge over decades how to connect to a variety of machines out in the field. But what do you then do with the data? The data as such is the base. But you need to bring it up to a compute layer. That's why our two companies together innovated in the area of edge computing, Siemens industrial edge as the platform, and together we developed applications that run on top of this platform, feed up data to the cloud. You can think of it similar to an Apple Watch that you can measure the heartbeat at the person at the machine and this then goes up to the cloud for analytics and further use cases, feeding data to other sources and also back to the device. So this in a nutshell is what we've been working on. The partnership has been running for 11 years. We were here already last year 2024 showing you the first case of the application of what we've been doing together and today is the time that we take you to the next level. Last time we talked about the first uses implemented and now we are all about scaling. Cloud computing is about scale and together we worked on the concepts how to also scale the use cases in the factory environment. And I'm really happy to be here with Marvin today as the factory in Alangan is only 50 minutes drive away from my place. So Marvin, take us through the great use cases you've been implementing.

M

Marvin Herbach17:39

Yeah, thanks Henning already for the introduction of AWS. So let's start with our factory introduction. Electronics factory Alangan was established around 50 years ago and is really already a brownfield factory. So we are now optimizing a lot of different production lines to get all our productivity gains all the entire chain. So you can see we have here motion control as a business portfolio element. So we produce so-called inverters. This is a cinematics portfolio element and we also have the cinematic which is the control. All in all it's the intelligent setup to drive the motor. So we have the intelligence and we have also here the inverters who do the power electronics. So it's all about translation and logic signal to the drive. And by also having so much different product types, we have different product variants to produce. So we have here a mid volume to high mix production. So it's a lot of different products which can be configured by the customer itself. That means we have also a heterogeneous production. So it's a lot of challenges to optimize to get it further smooth running. And we implemented also in the last several years over 100 AI models which are running on the shop floor now. And this was also already awarded last year with the World Economic Forum as a lighthouse factory. So we are also proud member here. And now we want to show you a few examples of how we improve our production daily basis. So here you can see a so-called THT assembly line. THT is a through-hole technology process. So you can see here typical product of us. So we have here different components of different size. It's like solving a puzzle but just in a bigger size I would say. And the first step is putting all the components in a place which is here the assembly process. So it can be done by humans or robot depending on our vision here. And then we have to check if everything is there and this is the first use case. So we have here an AOI, an automatic optical inspection, to inspect all the quality of our placement. Afterwards if everything is placed then we have the soldering process. And for the soldering we have now here a new vision use case which is all about checking the quality of so-called flux. And this is a transparent fluid which can now be inspected by using a thermal based camera to check the quality if everything is straight, everything is more or less glued together. And here we also introduced a new function for our industrial edge. So in the past there were only normal cameras supported. Now we can use also thermal based cameras. After gluing everything together and having the soldering done, we do a so-called AOI again which is an optical inspection that inspects the quality of the soldering. And here typically AOIs have static rule-based inspection. And by further optimizing this, we use digital tools after having it improved by lean philosophy, we can use digitality tools to further reduce your so-called false positives. That means if the AI says it's a fail, typically a human has to inspect this if it's a real error or not. So we have a manual touchup and now the AI takes over this role automatically. We have a reduction in productivity or increase in our productivity, reduction in our manual efforts. And finally we also have a so-called coating process. You can see shiny surfaces here which is the coating of our process. And we have here as well a low cost inspection made together with smart algorithms, which is low cost but using also cloud for scaling it across the factories and cells. So all in all you can see four different use cases using exactly same stack on all, made together with AWS.

H

Henning Hudov19:28

Right and Marvin, what really impressed me a lot is we saw here also what we at AWS call a flywheel. The typical Amazon flywheel is that if you're reducing cost, you're attracting more customers. With more attracted customers, you increase the number of sellers on AWS, and with more sellers, more variety comes, and again you get more customers in. Then the next round of this flywheel starts. I think what we're seeing here in practice is you also putting in or us together putting in a flywheel. The first use case that was the heavy lifting building in security as job zero initially. So can you talk us a little bit through how long did the first use case take, how long the second, how much could we then spin up this flywheel?

M

Marvin Herbach20:15

Yeah. So indeed the first use case here number one was all about five to six months. So we did all the customizing and also all the setting up the architecture once together with AWS with all the partners here. And then we used this blueprint for all the other use cases. So in less than two to three days we have already implemented this on our production cells. And the last use case which is the coating was running on day one already. Really impressive.

H

Henning Hudov21:30

And also here if you look what is now the target also for our future, this is so-called future automatic manufacturing. We have here again the production line and we have AWS as a cloud system but we want to also run further algorithms, further optimization. And you can see here all running typically on AWS but to get everything connected, we use here our industrial edge ecosystem as a clue as an intermediate layer between IT and OT. And we have running now the different use cases but also it enables us in future to work here much closer together enabling closed loop by using an AI model to control the other one. Typically approaches to Agentic AI, I think also AWS is working on this topic as well. What is your vision as well?

M

Marvin Herbach22:15

Yes, I mean what we are seeing is more and more the promise of Industry 4.0 now also gets delivered with the use of generative AI. There's so much routine work you can offload and simply have an AI running in the background doing for you, and you can check results again with simulation. So I think we will see a lot of improvements in the years to come. We're just at the beginning, that's for sure.

H

Henning Hudov22:44

Now let's have a look how we together set up our solution which we mentioned here. You can see here the typical build to run cycle which is the MLOps, the machine learning operation cycle, and it goes hand to hand from edge to cloud together with Siemens and AWS. And we want to show now the entire cycle how it's working here with our product portfolios. So it's starting all about here the industrial edge on the shop floor level. That means on field level we have everything connected with our edge. So we collect the data from machines like image data, we collect it from cameras. Here you can use so-called vision connectors from Industrial AI suite which is a product portfolio from ourselves. Then we have a lot of different other data sources and it's all together in our edge ecosystem available. Now here is also the running process of the AI model. That means the AI model consumes all the data, image data, machine data, and can do the prediction itself. So this is the optimization of the process here. And the results are then sent either to a machine to control it closed loop or we also send it out to the cloud. And here also AWS comes into place that we have a closed loop as well for the entire training and deployment.

M

Marvin Herbach23:53

Yeah. And Marvin, maybe before I jump into what we do on the left side of the circle, let's maybe also contrast how you worked in the past. My understanding was before leveraging cloud, you had to buy local compute and it could take you months until you had procured new hardware that you could use for these topics. Is that the case?

H

Henning Hudov24:40

Definitely the case. So in the past, our data center collected the data manually on on-premise systems or we also had different so-called pipelines. That means every use case was more or less a silo itself and it was not scaling across the different cells across the factories. For this we needed a repeatable standardized approach and came together with our solution here. Yeah.

M

Marvin Herbach25:05

Awesome. And I think what we now build together is as you see the swoosh to go to the left side of the picture. The data that's collected on the shop floor with the pictures and the machine data is then fed into the storage. On AWS side, it's with Amazon S3. That's our storage that has virtually unlimited storage capacity and it also brings life cycle data. Data that is not used anymore gets into very deep archives, very cost efficient, and it only needs to be recalled once or twice a year. But the data that's super fresh, you get it in a way that with latency you can draw it out in a fraction of a moment. That's on the storage side. On the compute side, we use together Lambda functions. This is again a computeless computing. That means you don't need to run the compute infrastructure yourself. You simply have an endpoint that you can trigger with APIs and it just works as an infrastructure. And the same is also true for what you see on this picture with EKS. This is our container platform and you can think of it that compute power as container is only spun up if you need it for your next job. So for example, next job comes, you need a graphical compute power so-called GPU, but these things are very costly. So instead of having them all the time on premises, you just as a container spin them up when you need them, you run the job, and once the job is done, then you redeploy it and you're saving cost as you are using the scalability of the cloud itself. Once this has been processed, then the data gets fed back based on the template approach that we invented together into the packaging. And with the packaging, I think it's back to you, Marvin, it goes back down to the shop floor.

Yeah, but maybe let's have a look first on the template approach. So this is a new one here. So in the past as mentioned, we have different silos for every AI use case. That means you have expert for this AI model, expert for this AI model. But the future is that for example the operator from the factory can itself operate all the AI models at once. That means we have a unified user interface which is doable or operable for every AI use case. And therefore we have so-called templates. You can take as analogy for example cooking in private life. In the past, everybody had for example an oven and fryer and mix depending on the food which you want to prepare. And nowadays everybody has maybe a mixer or an air fryer with a lot of different recipes and programs. You have a platform here and you select only the recipe which you want to eat. And the recipe is your exact template. So the data scientist who is creating the model is doing it always in the same way. Therefore we reduce the engineering but the operation is always the same platform. And the domain expert, the operator itself, can do now the operation from every AI model, vision AI model here, by themselves. And after getting the model which is then also packaged from this platform, we have as well here our Siemens SDK included ready for industrial edge. We have the deployment also automatically to the edge device itself. So here we have the so-called AI Asset Manager. It's like a hub system for the different edge devices which are running all around the factory. So it's like a factory-wide control system. And you can deploy the AI models but you can also monitor them. That means for example if one machine is not working well, you can directly see here drift and can react here either manually or automatically in future as well. And then we close the loop and have now the possibility to do this again for further optimization or for new use cases because it's scaling across the entire loop. So it's going hand to hand and we reduce reuse by using this kind of modular pieces in our engineering as well as in our operation due to platform here.

H

Henning Hudov29:52

That means now with all these recipes, you don't need to be a star cook anymore to have something that tastes really well. The layman so to speak can do it. You don't need IT experts to run this. Correct.

M

Marvin Herbach30:04

Yeah, that's right. So you only have once here the recipe creation I would say, but you can now use the star cook's recipe and can also enjoy it in every factory. So you can benefit in a factory network as well here. Yeah.

H

Henning Hudov30:16

So you're now even sharing the recipe book across the different factories.

M

Marvin Herbach30:20

Yes, indeed. Yeah. Yeah.

H

Henning Hudov30:21

Super impressive.

M

Marvin Herbach30:22

So, and now let's have a look on the numbers itself. So as mentioned, we're using here really this template-based approach which is here the platform which gives us a lot of engineering potential. So we talk about 60% here because as mentioned the data scientists can now focus only on the AI model and use the template-based approach. This is one of the first approaches here which we now implemented in our lighthouse factory. Secondly, as mentioned in our title, we can deploy it much faster now because we have the engineering, we have also the operation goes hand in hand, and we have an automatic deployment mechanism. So it's already in days available on the shop floor. If you have the PC already done on this kind of modular approach. And finally, you have then here the service cost because you have only one solution, one platform, you have only one service, you have not a lot of silos going on here, and you have a reduction in operation which is also beneficial for us as a factory.

H

Henning Hudov31:20

No, super impressive. And Marvin, can you tell me a little bit your experience? How are you now scaling this from one factory to the other? Are they coming? Do they see the benefits? Do they want to have your recipes or how do you actually do this in practice?

M

Marvin Herbach31:35

Yeah, so first after implementing this on one cell, we want to scale it internally at the factory itself. So we have a lot of parallel production here. So we scale it at a lot of different production machines. But we also scale it in our factory network depending on the other setup of the factory. They are interested maybe in the coating, maybe interested in our soldering use case. It's like a recipe. Not everybody likes the same food. So it's also a pull from the other factory. We have here a market internal market more and everybody can then share only the recipe because they're following the same platform. It's also scaling here across the factory because we are following the same language, the same platform idea, and only give here the recipe to the other ones.

H

Henning Hudov32:48

No, that's really impressive and I also love that you're not scaling just let's say in Europe, you're scaling globally. And I think again that shows hand in hand our partnership that we have this in different regions giving you also the latency for the compute that you need for these advanced use cases. So again super impressive that Siemens brings the global scale of how you bring this to production. And I think together we are able to serve you with the topics and the services globally so that you're able to execute this way.

M

Marvin Herbach33:27

Yeah. No. Nice. Then let's maybe have a look at the outlook. So today first day of Hannover Fair. We have plenty of opportunities to meet Marvin and myself. Either come to the AWS Pavilion in hall number 15 where we have a huge demonstration also of how small language models for production runs on AWS. And at the same time, you have the opportunity to also see Marvin here in Hall 27 at the Siemens booth to see all the other impressive things that we bring to market.

M

Max33:27

Gentlemen, thank you so much for joining us, Marvin, for coming here, for showing this great little exhibit here, and also to you for making your way over from the AWS booth. We wish you all the best for the fair and all your colleagues, and again, thank you so much for joining us.

U

Unknown33:58

Great. So, I'll get started off and then I'll hand over to Emmod. So one of the things I think that's important is Siemens is really in a large transformation to change from an industrial company to an AI-based company where we're really transforming into a data and AI-driven company. And that's a big change for us. So part of what we're trying to do there is if you look across Siemens, there's more than 700 product teams that deliver software to the market, and historically those things had different licensing, different foundations, different capabilities. And what we're trying to do with foundational services that I lead is to be able to have a common foundation for all of the Siemens accelerator products. So we want to build and deliver building blocks to the product teams. Those building blocks are for the whole suite of Siemens accelerator products. And then what we're also trying to do is to have an outstanding customer experience. If you have to log in to every product separately, if you have different licensing for every product, that's not a great customer experience. And so this is all part of what Roland leads us on on the transformation to one tech company. So foundational services is here to support that transformation. Now if I break down some of the things that we were just talking about there on the left, you'll see Siemens accelerator. So Siemens accelerator is our whole suite of products and how they work together. It's common identity, common licensing, it's a common customer experience, and being able to enable a land and expand sales motion so that once you buy something from Siemens, it's just an obvious choice to buy the second and third thing because it just works together on top of that common foundation. Then in the middle, you'll see capabilities that we deliver: SaaS services like identity and data services, edge services and edge application management, and on the right developer services. One of the things that we have tended to do is many of the products in Siemens had a separate tool chain for its path to production. How source code was managed, how quality was validated. It was many different systems. And one of the things that Roland has chartered us to do is to deliver what's called OSIS, one software engineering system, which would be a tool chain for all software products in the whole company. So that's a big transformation that we're just starting on but is that third leg of the stool. So when you think about what we do with FDS, we're enabling the businesses to focus on their business value so that we can do the undifferentiated heavy lifting below the covers. Now when it comes to Envoy, one of the things that we see is in our customer base, when we go talk to their CTOs or their CIOs, they have a very disparate system where the silos of applications don't work together as well as they would like to move data across the value flow. It too often takes human intervention where humans have to manually move data from system A to system B. And then there can be unplanned outages because maybe if somebody's off that knows how to do these things, you can't do the job, or maybe IT systems go up and down because they're different backends. So change that you might think should take a day or two can take weeks because of that manual flow of information. So we're introducing Envoy as a way to shepherd that data across these systems and to be able to have human-oriented interactions but as part of a controlled flow. So if you look at agentic workflow today, you can see great promise and lots of proof of concepts. There's great things out there where somebody will take a small problem and prove what an agentic workflow can do. But what we're trying to do with Envoy, which is based on top of AWS agent core, is to have a performant, scalable, secure system with governance where you can have that agentic workflow and deliver it as successful enterprise scalable agents that work with the products that you know in Siemens accelerator. So Envoy works, it connects to the data sources that you have, it connects to the applications that you know, and enables customers to deploy those workflows. And if you look at the right hand side here, we want to make sure there's a focus on configuration over coding. You can of course code, there's nothing wrong with coding, we love coding, but as much as possible, we like to enable configuration. Also, there's modularity, there's ability to maximize the customer's return on that. And the customer is free to choose their LLM of choice. We don't force that on anybody. So it's all about leveraging what Microsoft, leveraging what Amazon brings to the forefront of these capabilities, and we build on top of that. So with Envoy, what we're trying to do is if you look at example product engineering and manufacturing engineering products, we're really focused on four initial offerings: design center, sim center, team center, and opcenter. What we're trying to do is make sure that we can have workflows that span across those four different applications with a common foundation and the ability to have that agent workflow that moves data between the products as appropriate in a way that enables that workflow. All built on top of that scalable interface. So on the bottom you have our foundational services that we deliver, which are built on top of Amazon, which Emmod will explain next. And of course we're built to support DI SI and mobility in that capability so they can work on their application differentiation while we work on the non-differentiated heavy lifting. Emmod, do you want to talk about what we've done together?

I

Imad39:16

Sure. Yeah. So we started our journey like a year ago and during this time, we actually started to introduce to Siemens the new agent core services. Agent core helps accelerate the agent development with a multi-agent orchestration. So we planned for a workshop with Siemens in Pune and the first week of that workshop was actually focused to let the team experiment with agent core and learn about agent core capabilities. The week after that, we bring the ISW, we learn about their use cases and we start developing agents. So within one week, we developed nine agents including an agent orchestration layer as well with agent core. During that time in the workshop, we also identified some gaps in our service. We helped bring the AWS service team to learn about those gaps and identify how we're going to move forward on the next step. In addition to that, we bring ProServe, we have a program called resident architect. So this will help to actually move along with Siemens to make it in a production level. So that architect works almost on a daily basis with your team to identify any kind of development bottlenecks so that we can elevate this. So during that design phase, we have a few design principles. We start with configurability. We don't need the Siemens developer to actually update their code every time there is a new large language model or a new kind of configuration. So based on that, the developer doesn't have to update their code but update their configuration. That configuration could be swapping large language model or could be adding a configuration for bedrock guardrail based on their use cases. And then if we look back on AI agents, AI agent is composed of a brain which is the large language model, also include memory, and in addition to that also include tools. So for memory, agent core provide you with short-term and long-term memory, and there is a lot of work under the hood to transfer short-term memory to long-term memory and consolidate this into a long-term memory. So we leverage agent core memory for memory interactions. In addition to that, Siemens FDS built their own solution with S3 and OpenSearch as well. And then with the extendability, those agents require to have some tools. Think about it as your hands and feet. We have the NCP integration to integrate with data sources, with API, and with any other tools. And then we also have Amazon EventBridge to integrate with other services as well. And then for security and governance, we have the agent core guardrail or bedrock guardrail. We also have the agent core evaluation to evaluate the performance of the agent, and then we have observability which provides you with all traceability from invoking the large language model to the interaction with large language model and reasoning. So all of this is actually available as blocks for the team to look at it and see how we're going to improve the agent.

U

Unknown43:02

So I'd like to make a comment on that too because when you look at all of those capabilities from Amazon with Envoy, we're trying to unleash those capabilities into the Siemens products. We're not trying to protect the products from Amazon services. We're not trying to isolate them. We're trying to make it even easier to adopt and even easier to leverage. So in no way, shape or form is Envoy trying to protect the Siemens developer from these. We're really trying to unleash them, which is our attitude across all the foundational services. We use a ton of Amazon calls in our product offering. And we're not trying to protect the product teams from them, but we're just trying to make sure that we leverage all of that to deliver a multi-tenant, highly scalable, cloud-scalable offering to support all of the Siemens accelerator offerings.

I

Imad43:47

Right. And it's all configurable. So through your API interface, you can select what language model, you can configure it the way that you like, what guardrails and so on, so very simple to use.

U

Unknown44:02

So with agent orchestration service, your team stops building infrastructure and focuses more on building intelligence. And that's actually the main role of Envoy platform. So with that foundation and AI services, it makes it reliable, scalable, and secure. Now we're not talking about a roadmap, we're talking about a solution and a service already in production today and already adopted by many business units.

I

Imad44:30

Yeah, we've got at least four examples where products are using it in production and we will continue to make it available to all the rest of the Siemens Corporation because we don't want every product team to have to be making this investment time and again. We'd like to make it once and then leverage that investment across the Siemens accelerator portfolio.

U

Unknown44:48

Right. And we're looking in the future to actually innovate more with Siemens, right?

I

Imad44:51

Not just on AI but on other services as well.

U

Unknown44:54

Yeah, absolutely. Yep. And if you want to learn more about our capabilities and our services, we have Siemens booth in hall 27, that's our booth here, and we have another booth in AWS in hall 15.

M

Max45:15

Thanks very much. And yeah, another great example of our ever-expanding partner ecosystem. Our partners are with us across our entire booth because we believe that true digital transformation is only possible through a collaborative approach. No more solo efforts. That's why we are teaming up with the likes of, as you just saw there, AWS, but also Accenture, Capgemini, Microsoft, Deloitte, and many, many more. Plus a broad network of system integrators and distributors who are helping us create an environment for industry that is flexible, resilient, but also future ready. Now in addition to partners and also customers who are with us here at the booth, we also have the partner country. So every year the Deutsche Messe, the organizers of the event here in Hanover, they have a partner country and that partner country has its own area at our booth. And this year the country is...

N

Narrator2:46:24

Brazil. And Brazil was in fact the first ever partner country of Deutsche 45 years ago. And we at Siemens have been active in Brazil for 158 years. That is when we established the first telegraph line in Brazil. And that historic commitment to data, to connectivity and to technological advancement has evolved rapidly over the past few years. That is why we are incredibly proud and excited to showcase what we are doing for both the people and the country of Brazil. So, let's take a look.

C

Christine2:48:27

We're here in the Brazilian corner of our fair booth in Hall 27. Brazil is partner country of this year's Hannover Messe. And with me is Pablo Fava, the CEO of Siemens in Brazil. Pablo, how was your experience here being partner country and the overall impression of Hannover Messe?

P

Pablo Fava2:48:47

So, thank you Christine. It's a very nice experience actually. We have been working for years in order to become partner country. Brazil was the first one in 1980, the first country that has been partnered in this fair. It is a big job but it's a big opportunity also to showcase everything that we are doing in Brazil with our partners, with our customers, and to bring a huge delegation here, not only customers and partners but also institutions and government. It's a good opportunity to connect with people. So I would say very proud of everything that we have achieved here.

C

Christine2:49:23

And we had a lot of customers on stage talking about Siemens solutions. So definitely that was very impressive and also what you have achieved here in the booth with the setup, inviting customers coming here talking about it. So great experience and there is one gentleman already eagerly waiting to get a chance like this. We have Fernando Silva, the CEO of Spain, the next partner country next year Hannover Messe 27. Fernando, could you share some insights on Spain?

F

Fernando Silva2:49:54

Yes, first of all, congratulations Pablo and the Brazilian team for the outstanding work you did. We will learn from you certainly, but let's talk about Spain. Let me frame it in five topics in terms of the dynamics of the Spanish economy. The first one is our geostrategical location. We are connecting Europe with Americas, with Africa, with Middle East and this is a unique asset that we have in Spain. Second, we already have a very dynamic industrial framework. We are very strong on machine building, on defense, on the automotive sector. So we need to build on top of this. And how can we build on top of this? Adding the digital layer. So connecting the digital and the real world, putting AI, putting connectivity on top of everything. And finally, two very important topics. Spain has a very competitive energy environment. Our energy is mostly renewable and very competitive. And I think we also have a unique capacity to attract and retain talent. Our people from engineering are very strong. So I think we have all the factors to make it a success also in Hannover 27.

C

Christine2:51:00

Sounds promising and we're curious what's going to happen next year. So we're happy to have you hosting and being the partner country 2027 at Hannover Messe. Thanks Fernando. So Pablo, why is Hannover Messe so important to Siemens as a whole?

P

Pablo Fava2:51:16

So Hannover is a moment in the year where we have the chance, Siemens as a whole worldwide, to bring customers, to bring partners, to showcase everything that we are doing in terms of innovation. And we have to transfer this somehow and it's not only through digital ways or doing in our countries in our regions, we are normally doing this kind of road shows with customers, but coming here to our home to Germany, particularly Hanover, where we also can see other competitors and the strength of Siemens compared to other competitors. That's a very strong point to point out why we are the enablers of the technical transformation of the regions where we're acting. For us in Brazil, Brazil is also a country with nice resources, huge resources, with sustainable energies. 90% of our electric matrix is already sustainable, so Brazil can be an answer also for the future. It has a nice opportunity to participate now.

C

Christine2:52:23

Great, great feedback and it's big footsteps actually which you're stepping in, Fernando, with being the partner country next year because Brazil definitely showcased a lot of great solutions, happy customers. So we're looking forward to have you here but now is the moment that we hand over the baton. Are you looking forward to that, Fernando?

F

Fernando Silva2:52:46

Yes, absolutely. And again I think Pablo already mentioned the most important is that we work as an ecosystem with our partners, with our customers, with universities to make the best out of the technology. So we are really looking forward to showcase the Spanish industry, the Spanish infrastructures and how we apply technology, but also to reinforce the connection between Germany and Spain to really make a more competitive Europe and a more sustainable and fair Europe. So I think the learnings from Pablo and the team will be great and again we have to work as an ecosystem to make the world a better place to be.

C

Christine2:53:24

Wonderfully said and I think now really is the moment to officially hand the baton over from Brazil to Spain.

P

Pablo Fava2:53:34

Sure.

C

Christine2:53:34

Fernando, as an Argentinian living in Brazil, it is my great honor to transfer to you the baton to a Portuguese living in Spain. Right.

P

Pablo Fava2:53:43

Yes, exactly. And I wish you a lot of success for next year. Be prepared. It's a big job but it's a big also realization.

F

Fernando Silva2:53:51

Yes. Thank you Pablo. It's a great honor to receive it from you. In addition, we have all these connections Brazil, Portugal, Spain, South America and so I look forward to also work together with your team to learn on your experience and build a very strong Hannover 27. Thank you very much.

C

Christine2:54:11

And see you soon.

F

Fernando Silva2:54:10

See you soon.

P

Pablo Fava2:54:11

Thank you.

That's a wonderful experience here. I love Hannover Messe because the proud to be Siemens moment definitely comes true. Thank you.

M

Max2:54:27

Thank you very much. And we're going to be handing back over to Christine and Miki in just a second. But first, I want to make a few final comments here on the stage. I just want to give a brief overview again of what you've been experiencing here at our booth from an event experience perspective. You heard just then the partner country. Brazil, every partner country gets their own representation here at our booth. But of course, there is much more going on as well. We have our customers represented here throughout the entire area. I want to pick out three in particular who are in our digital enterprise showcase for the consumer packaged goods industry: PepsiCo, Natura and Pringles. PepsiCo is using our simulation technology to optimize their warehousing and intralogistics operations. Natura, a Brazilian cosmetics company, is using our digital twin technology to optimize the way they extract essential oils. And Pringles uses our simulation technology to simulate the dough and can filling process. In that digital enterprise showcase, we are demonstrating how with our core company technologies - the comprehensive digital twin, software-defined systems, and industrial-grade AI - we can help get the product from design all the way through the supply chain to when the product hits the supermarket shelf. In the middle we have our technology deep dive area with four islands representing our digital thread approach: advanced machine engineering, smart manufacturing, systems engineering, and electrification and buildings. On the far side, we have an animation showing how we envision the future of industry dominated by AI, making everything more autonomous, flexible, and orchestrated. This area is split into three sections: a shoe sole exhibit using additive manufacturing, physical AI with robots and humanoids, and smart infrastructure where AI takes care of maintenance, operations, and sustainability. That is our booth here in Hall 27, our new home with a focus on industrial-grade AI. I'm going to say goodbye for now and hand over to Christine and Miki.

C

Christine2:59:23

This co-pilot of mine called Max definitely did his homework as I always say and I wonder who is going to tell all these stories from tomorrow onwards. Probably his friends and family and Julia his girlfriend is going to get all that information now firsthand from tomorrow onwards. How was your Hannover Messe experience?

M

Max3:00:00

It was amazing. I'm completely positively overwhelmed from all the things that I've seen here, all the amazing people I've talked to and generally the amazing vibe we had here. How about you? What did you think about it?

C

Christine3:00:42

I mean to me Hannover Messe is very special. I'm 25 years within the company and 12 years definitely we have been working on that stage program which evolved year after year and the whole crew here who is working on that program grew to a family. At this place is the time to really say a big thank you to everybody who involved to create this, to produce this, to edit this, to bring it to your tables, to your devices wherever you are watching. It's a great honor to really work in that team, to trust in everybody who is involved, and this is actually my best Hannover Messe experience in regards of what we achieved in this 12 years time. Hannover Messe is a crazy time and if you have the virus for a fair you definitely live and breathe Hannover Messe, innovation, exploration and all these great things we're showcasing here. The team on site especially is also so cool because without our experts, with our partners, with our customers, we could not host a program like this with 250 plus speakers with 180 topics over the course of the week. And Max, you're joining us now. Great you're back. I mean, I don't know if you heard it, but I wonder whom you're going to tell all these stories, what you have developed and worked on and learned from tomorrow onwards. Port Julia.

M

Max3:01:28

Yeah, I think I'll just tell my girlfriend Julia every night. I mean, as you do as well, when we practice and rehearse for these things, you've told me as well, you walk around your neighborhood at night speaking to yourself. I do that, too. I think I'm just going to continue talking about partner countries, about partner ecosystem, and customers. They're used to it. So, I'm just going to keep on doing that.

C

Christine3:01:48

Okay, keep on doing that. I keep on doing to say thank you to our partner country, Brazil, which was really a great experience. And we prepared a little song here which is kind of like in Hannover at the fairground. We've had fun. We've had partners and customers. We explored our exhibits at the fair booth. Always a pleasure to host these sessions for you all. Now we're traveling to the Copacabana. Something like this. We're going to prepare on that. Big thanks to you, Miki. To Izzy, who's probably watching us at the airport right now. She's flying back home to Manchester. Izzy, great that you've been supporting. Also to Tina in the office, to Carsten backstage, to Cedric, to team Comp team, to the GBS Dream Boys, and to many more who have been involved. And as always, Christine, to the lady without whom this stage program wouldn't be here, the queen of the show, you yourself. You've put together another amazing program. This time with a jam-packed gallery studio as well, Monday to Wednesday.

M

Max3:03:06

We forgot Militia. Militia, great host on stage in our gallery studio.

C

Christine3:03:11

It's an absolute jam-packed thing. Once again, you made it work. We coordinated ourselves. We rotated and it was an absolute dream. So, thank you once again. Without you, this wouldn't be the same.

Well, my co-pilot, I have trust and faith in you, dear Max. So, dream team once more. I hope you all enjoyed watching this great show. And we just have a highlight video now to kind of take impressions from all week long. Get the highlights. And if you want to see more of our sessions, they are still available on demand. Enjoy. Stay safe, stay curious, stay innovative, and come back latest on this channel for SPS 2026. Goodbye.

M

Max3:03:54

Bye-bye.

N

Narrator3:03:56

Now, we have to innovate. We have to push the boundaries of what is being able to be done. We're basically unveiling the future. You have to first prove that it works. And I think we proved it, right? Welcome to Hanover Method 2026.

When it comes to AI. No company can do this alone. We really need strong partners to make this happen.

This is where people exchange, where ideas are born. Possibility basically takes shape.

Now think about how many products we already used today. Yogurts, toothpaste, shampoo, coffee. Consumer packaged goods companies must handle rising demands for diverse and sustainable products. How can they manage this complexity? With the power of data, seamlessly combining the real and digital worlds. Siemens' leading industrial software and automation portfolios enable the digital enterprise, where everything is connected by fully integrated and digitalized workflows. This end-to-end approach enables a horizontal flow of data from design to realize to optimize. Digital threads guide you through the most efficient way on your digital journey. Siemens Accelerator provides access to the entire portfolio, ecosystem, and marketplace, powered by industrial AI. AI makes sense of vast data, transforming it into actionable insights. With the right data fabric and knowledge graph, companies can accelerate product development, optimize production, and achieve results like Pringles' 10% higher capacity, Natura's 50% lower energy and water consumption, and PepsiCo's 20% higher throughput. The digital twin composer brings the industrial metaverse to life. Next time you go to the supermarket, think about whether that product was empowered with Siemens technology. Come to Hall 27 to explore the end-to-end story.

S

Studio Host3:22:16

So welcome everyone. Good afternoon. I have the luxury of presenting this next panel and with me and in order I have Cedric. I sure you know everybody knows Cedric is the CEO of Siemens Digital Industries. In the center I have the luxury of having Ali Perroi. Ali is the VP of supply chain and manufacturing. And in the far end I have Stuart Makuchin. Stu is VP of industrial metaverse, been in the company for few months.

S

Stuart Makuchin3:23:02

29 years.

S

Studio Host3:23:10

29 years only and is responsible of the industrial metaverse strategy. So, first of all, I'd like to start with Ali. Ali, first of all, welcome to Hannover Messe. Welcome to the Siemens booth. So, thanks for having me. Really happy of having you here. So, tell us a little bit about this project. What is this project interesting for PepsiCo? Why what do you want to get from this project that we were presenting at CES this year and now today at Hannover Messe?

A

Ali Perroi3:23:28

Yeah. So the demand for our product is growing but our footprint isn't. So the goal was to do it in digital first to make sure that we can expand manufacturing into the warehouse, make sure the lines that we were planning to add fits, figure out all the flow, figure out all the inefficiency if you will before we actually spend any money, any capital doing the actual work. So that was the main reason and we had food beverage feeding into the same mix instead of a large warehouse. So we wanted to do it digitally first to reduce risk. The main reason that was the project.

S

Studio Host3:24:12

Yeah. I think it's an interesting thing that of course you can see in our booth. But this is not just a digital twin of a line or a machine. I think this is something more than that. Why do we think that this is a milestone in our industrial metaverse strategy?

S

Stuart Makuchin3:24:27

First, let me say thank you to Ali because I mean if we think of PepsiCo, we have a long-standing relationship but the great thing is we're in deep admiration of what you do. I mean you serve billions of customers. You have billions of data touch points and the key question was how can we make that better, right? How do you find somebody you partner with to rethink the fast-moving consumer goods or packaged goods industry? And that's why thank you for letting us work with you. And what is actually very interesting is we always envisaged to say if we want to do something digitally it should be simple, it should not be difficult. So we built the digital twin composer together with Nvidia and Pepsi world premier the first one which is using it and you have to imagine it is that you can sort of simulate and build scenarios extremely fast and extremely quickly. And because you have that opportunity to do this, this is what we wanted to actually drive forward with.

S

Studio Host3:25:24

I think we have a video here.

S

Stuart Makuchin3:25:26

Yeah, we have a video, but we have better than a video. We have a video and we have a voice over and Stuart, which is sort of with this only 29 years old. Exactly. Background has built it forward. So let's roll the video and then tell us a bit what we've done with PepsiCo, which technologies there's a lot of technologies coming together and why this is super different.

So this is the application we developed for the showcase for PepsiCo. It's what we call a single pane of glass. So we can look at different plants. We can actually look at the supply chain flow between those plants and the goods in and out. We can look at different aspects and what's happening behind the scenes. It's pulling data from all different systems. So this is Teamcenter. All the information needs to be managed in a secure manner. You can fly through the current state of the plant. Now, this is leveraging our NVIDIA partnership that's embedded. This is the current state, but one of the things you want to look at future states. So, I look change the date and in the future state I've dropped a Gatorade line into this plant. So, I have this concept of effectivity. I can look at different things, but this is a single pane of glass. There's information coming from 20 different systems behind us and every aspect. There's a digital twin. So this is a digital twin of actually the mixing tank. So it's a single experience that you're pulling all this information in a very seamless way. And this is just part of it. The full demo is available on the stand.

S

Studio Host3:27:02

Yes, Stuart. Thanks so much.

That's fascinating. Ali, let's roll back a little bit on time. What were the operational challenges you're trying to solve with these models that this industrial metaverse project you did with us?

A

Ali Perroi3:27:15

The biggest challenge was we were going to make a lot of decisions in a very fast way and we wanted to get it right the first time and minimize our investment and mistakes. So the best way to do it is the digital first approach. Do it all in digital. Technology is there. The main reason we partner with Nvidia and Siemens to do it in a scaled way because we plan to not only do it in this region, we have many regions that we want to do this in. So we wanted to do it fast. I would say what it allowed us to do is make better decisions faster and that was the main reason.

S

Studio Host3:27:54

Yeah, a good reason.

Good reason. Yes. And I know that we're still a little bit early in the process, early on in the journey with we're starting with you, but can you advance us a little bit of the advantages and the gains we've got so far with us?

A

Ali Perroi3:28:10

We were able to identify where we had bottlenecks as we add the new line. We realized we didn't have enough docks. So we ended up using an auto truck loading system that allowed us to speed up the pallet that's coming off the line. Get it out the dock. We were able to optimize it because we didn't have a lot of space. All of this inside the 12 weeks. So we were able to prove that everything fits and flows digitally first. So now I'm happy to report that that project is actually expanding. They're asking us to look at can we add two more lines in this same facility. So that's phase two that's coming up.

S

Studio Host3:28:55

That's coming up. Stuart, you've been in this project since day one. You're one of the sponsor executives of this project. So which are the main challenges we had to face so far.

S

Stuart Makuchin3:29:06

So I think the biggest challenge was data. You know Ali was very good. They gave us three simple plants. They're 50 years old. There was no 3D data. Data was in different silos. Some of it wasn't even electronic. So pulling all that data, we scanned the plants. We converted those to 3D models. We then use those to simulate physics-based simulation and optimization of as-is and to-be state. And this all had to be in a managed environment. And then just on top of that, we gave us 10 weeks to do it. It's a lot of technology just working together seamlessly from physical to digital, from digital to physical again as many times as needed.

S

Studio Host3:29:51

That's fascinating and Cedric, but PepsiCo is not a small company, they have more than one plant, more than...

C

Cedrik Neike3:30:01

They have 300 plants. 300 plants. Yeah, exactly.

S

Studio Host3:30:04

So, what are the challenges we had to face to scale this?

C

Cedrik Neike3:30:04

I mean, look, you have to first prove that it works and I think we proved it, right? The amount of capex to redeploy the lines, the idea was how do I do with less footprints and more flexible environments. So the first thing was can I actually make this profitable? So I think it's 20% throughput increase, 15% less capex. It's actually a great view to do it. The second thing which is great because it's modular, right? It's really the capability to put these things together. We can now apply it to other plants and actually expand it and that's what we really are going for. And this digital twin composer is something which we developed with Nvidia and which really enables us to do this and you're the first one we're deploying it with. We hadn't expected that you would move so fast and we have been moving at that speed with you and now the question is can we actually move it to the rest of the environment. And then there's certain really cool things you could do. I don't know, you have your Gatorade with you, imagine that there's a big football game or a big soccer game wherever country you're from. What happens is that for drinks there's a spike. So that could be a Pepsi, Max, Mango. And we need to build this as soon and as close as possible. We build up the capacity and then ramp it back down again. And with that digital twin composer, we can do it. We can reconfigure the supply chain and we can reconfigure the environment. So PepsiCo is cool because they're fast, they give us tough problems, they're scalable, and they're looking into the future to be even more adaptable. And these are making us the ideal partner. Exactly going in that direction.

S

Studio Host3:31:40

Man, Ali, I don't know if you want to if I said everything correctly or if you want to correct me.

A

Ali Perroi3:31:45

Digital composer allows us to streamline the workflow. So we are one of the first ones I understand to use it and yeah, you can kind of see the physically see the decisions you make and how they materialize all in digital world before you actually go to physical. So that's a big advantage.

S

Studio Host3:32:07

Ali, just one for you. We know that you are very aggressive in the way you want to deploy this technology across the different sites but what's going to be the next plans for you, what do you have in mind?

A

Ali Perroi3:32:19

So our goal this year is to scale this capability across not only North America but LATAM, EMEA and Asia. Ever since the announcement at CES, all of our country GMs are asking for this capability because they have plants and they want to test it in digital first. So our goal is to not only scale it, but to show value right away. I would say show value and do it often.

S

Studio Host3:32:52

Absolutely.

And Stuart, you've been in the industrial metaverse since the beginning. So you're one of the executives that have been pushing for this technology, one of the visionaries. We have a lot of visionaries inside Siemens. But we have been one of the ones that we're visionaries and we're executioners and you have both. So you actually make things happen which is quite important. What's next? What's the next thing that we should expect in the industrial metaverse from?

S

Stuart Makuchin3:33:06

Well, I think this world is accelerating, right? I think digital twins are going to get more comprehensive. You're going to be able to do physics-based simulation of every aspect to give you insights into products. AI, we're scratching the surface of what AI does. AI is really going to help us deliver this at scale and really accelerate it, right? And so there's all these multitude of new use cases. I could go on. There's around humanoid robots, virtual commissioning. We're envisaging all these new use cases that we haven't even thought about because once you bring all this information together using our digital twin fabric, AI fabric into a single pane of glass, it enables so many new things.

S

Studio Host3:34:05

Yeah. And the last one for Cedric, I'd like you to use your crystal ball and not just for this industry. We're explaining how this industrial metaverse can change the food and beverage industry. But how do you see industrial metaverse impacting the industry in two, three years?

C

Cedrik Neike3:34:22

So I have to give you a little secret. I am and was a gamer, right? And I love playing Sim City. I love playing also the more sort of interactive, we shan call them cannot call them shooter but real time 3D first person. And the dream was always could we make our industry as fast, capable, and as much capable of looking into the future than anything else. And we have achieved that. And I think this is what we really have done is we talk these ultra realistic 3D perspective with the capability to simulate because what we do is actually we call it shift left, we shift the problem from solving it in the real world into the digital world. And in the digital world, you're not constrained by brick and mortars. You're constrained by how much compute power you throw at a problem. And it's been one of the most exciting partnerships, one of the most exciting capabilities we have because we shown how fast this is possible. And I don't think we had a lounge which has generated more interest in short period of time. We have 350 customers which are wanting to work with us at the moment and we have blocked the rest because we said look we have to consume that Pepsi being our absolute number one, you're our number one and we're working with you. But this has really hit a nerve and I think that for us to actually do exactly what we have is to understand the real world, build the digital world to have...

U

Unknown3:35:45

The digital twin accelerate them with AI and really have a bottom line impact is something which is super powerful and I have to say we couldn't have done it without you guys Stuart and definitely a customer which is pushing us but this is the new standard and you should have a look at it because I think it's super impressive.

Mhm.

S

Studio Host3:36:05

Thank you very much. Uh gentlemen just to close this panel. It's been a luxury having you three. I would like to encourage you just to step by the CPG booth. We have an amazing demonstration of a pop-up factory also done in partnership with PepsiCo that shows how can we do a fully automated lights factory running with AI. So that's a really interesting thing to watch but also you have all the projects that we done with PepsiCo. Just thanks so much. We love having customers like PepsiCo that they push us that they let us show all our technology and I wish the rest of the audience an amazing Hana Vermesa.

U

Unknown3:36:46

Thanks so much.

Thank you. More to come.

Thanks.

Thank you very much. Well done.

S

Studio Host3:37:06

Great you're joining us and I have to say first of all thank you Charine for those wonderful gifts which you sponsored here. Every external speaker gets those gifts and they're all happy because usually we don't have those nice treats to bring along. So thank you very much for their kind gesture in supporting our stage activities here. A little bit of a treat and a feel from Brazil. So I'm glad people are enjoying them.

U

Unknown3:37:32

Very exclusive. So thank you so much.

S

Studio Host3:37:34

I'm going to do a quick introduction. So you got the who's who. We got Judith Visa. She's member of the managing board at Seammens and she's the chief sustainability officer and also my boss in regards of people and organization. She's the head of our people and organization so responsible for HR as well. Thank you so much, Judith, for taking time coming here. And we got the global ambassador for the Brazilian company in cosmetics, Natura. Jeremian love. I love your last name. That already brings fun and how shall I say simp. So most panels here actually are deep core technology and large-scale industrial automation and AI as a matter of fact when we look around it's everywhere. We're discussing now something very very different. We talk about the digital transformation of a small set of communities in the Amazon rainforest. Now to I'll start with you: how did this project come about to Semens? How did we get involved?

J

Judith Visa3:38:50

Well, I think it's the magic of a long-standing customer relationship that we have with Natura for the last 15 years. Natura's deeply rooted knowledge and connection with the Amazon communities. So, I think for over 20 years and COP. Yeah. So this actually was the trigger point to say how can we actually do something as Semens that is truly bringing technology to Amazonia.

S

Studio Host3:39:20

Sorry if I just may introduce COP 30 in BM conference of the parties last year end of November.

J

Judith Visa3:39:27

Yes. Exactly. Now thank you for that. And so there was a number of things that we wanted to do to bring technology to the Amazon. But in this particular case, and that's what makes it so special, is that we're partnering with Natura who know this so much better and have such long-running relationships. And this is really all about making sure that we preserve the tradition of what is the communities in the Amazon, their knowledge about nature, but then to marry that with technology. Some good Industry 4.0 digitalization technology that we can actually bring to a far away place. And you're right, the scale of this particular initiative is small, but it does have the opportunity to scale together with our partner. And what we really wanted to make sure is that we set an example, and you said technology with purpose, that we set an example of how we can actually cherish the nature that is not just important for Brazil but for the world. The lung of the world with regenerative practices, infused by modern technology, and really be able to lift up the community also in terms of skills and prosperity.

S

Studio Host3:40:47

Yeah.

And from your perspective, how do you see that collaboration amongst us?

J

Jeremian Love3:40:54

Well, I think this has been a beautiful partnership since the very beginning and I think it is because we have this sense of mutual respect. As many of you will know, Natura is a Brazilian-based company. We've been around for a very long time operating in the region. And in the Amazon in particular, it's actually 25 plus years that we have been working and cultivating these relationships. We also have a real commitment to the forest itself. So we have already worked in partnership with others to help support and conserve 2.2 million hectares of the Amazon forest. For those who may not think in hectares, that's about the size of 15 São Paulos. So it's a really big part of our business being close to the forest, protecting it, and because we have our factories operations in the region of Belém, we have this real close sense of proximity. But another really important part of our relationships as Natura are with the traditional communities and the indigenous peoples, the organizations and cooperatives where we source the ingredients that we use to make our products. I think there are three words that come to mind that ground this conversation and this partnership. One is this shared belief in the idea of symbiosis, that we can find ways to lean in and understand the connections between people, the forest, the environment, and business. Symbiosis of how those things interrelate, and that symbiosis can lead to, in the case of Natura and our relationship with Siemens, a real support to champion the sociobioeconomy. The sociobioeconomy is where we create economic models that allow us to keep the forest thriving, the communities thriving, and also have an economic model that is viable and successful for business. So I think this was a really natural partnership, pardon the pun, because we're talking about nature, but a natural partnership because we are absolutely values aligned. We're both deeply committed to the project and importantly the people element, knowing that these are indigenous and traditional communities that have really important wisdom. And I think we also share a deep belief in the power of partnership, that we can go so much further faster when we operate together. So it's a real joy to be here talking about this partnership. Thank you.

S

Studio Host3:43:26

Wonderful. Thank you so much. Great words. We're humbled, I have to say. So what kind of ground challenges do these essential oil communities face in the Amazon? Well, let's actually visit one of these communities, Apro Comp, which is I think the one where this project is grounded, two hours outside of Belém where the conference of the parties took place. It's a place rich in traditional culture and history. It's a place where they dance the carimbó dance, where they do the scent bass, the bay dishes. So a place rich and full of tradition and community. Now this cooperative is really brilliant because it's actually run by women. Josie is the woman who leads this cooperative. I had the great pleasure to go when this processing facility, this agro-industry, was opened in 2024. I got a chance to meet the team and really experience it. I wanted to share something: that day they gave some candles with scents from ingredients harvested in that region. In Portuguese it says, 'There are days that mark your soul.' For me, visiting that community really marked my soul. Every time I need a revisit, I smell it. You're more than welcome to take a smell because it's a place that marks your soul. So again, a place with rich culture, tradition, history. When it comes to that agro-industry that the community runs, they use traditional models to process the oils, steam-powered processes. We realize those systems are done in an analog way, labor intensive, dependent on operator intuition. So there is an opportunity to increase yields and make it more efficient in water and energy use. The question we asked is how can we modernize this important work while maintaining what makes it meaningful, the connection to traditions. We were thrilled to connect with Siemens because the more efficient we can help make those communities, the more value stays in the community. So it was wonderful to build this partnership together.

So how did we get involved, Judith? How did it start?

J

Judith Visa3:46:02

This is where I'm getting a little more technical now. But it's exactly what you said. A lot is preserved by tradition, based on intuition. The question was how can technology capture some of that and make it more repeatable and better. So it's building on what's already there, making it more reliable and efficient. This is small operations, small communities, but technology can do the trick. We created a digital twin of the extraction vats, where the oil is extracted, involving steam flow, temperature, pressure. We've been able to halve the water and energy consumption, lower the pressure, and monitor it remotely, which also helped from a safety perspective. It comes with upskilling the community. All of that together allows a circular, regenerative approach and lifts the community in prosperity. Sustainability in this case is not just about the forest, but about a lasting impact that sustains itself by giving people agency and tools through a relatively small investment. We think this can be scaled and repeated in different places.

S

Studio Host3:47:48

I mean when we talk technology you think of high industrial places, especially when thinking of Siemens it's always large projects. I wonder, Charine, how you were able to introduce these new technologies to traditional communities and processes. I guess that was not the easiest part in convincing them to go for something very different and to use that as a blueprint for future projects.

J

Jeremian Love3:48:16

Yeah. I think it's really important to note that working in co-creation with the local communities is critically important. You used the word agency, that's a really important word about making sure they have the power and ability to be in control of the process. It's the two of us here today, but really it's a triangle of partnership: Siemens, Natura, and the Apro Comp community. We work in partnership together. Some of the ways we can look at blending different forms of intelligence: you mentioned AI, artificial intelligence, but there's also ancestral intelligence. Bringing these two forms together is important to modernize communities and operations while ensuring the community maintains control and agency. In this project, that involved working and learning from traditional processes, training on new technologies, but ultimately making sure operational control rests in the community. The benefits are three win-wins: rainforest, people, and business.

S

Studio Host3:49:44

Still we are talking about a cooperative, just small groups deep in the Amazon. Do you believe a project like this, Judith, of this size can truly apply to a global technology company like Siemens? It's two totally controversial things. So I think there's no contradiction because we not only work with large customers like Natura, but also with many small and medium-sized enterprises. Even if this is nano or small community, the minute you scale it up, take the insights and make them replicable, you have a model that equally scales. So it's a question of how we can continue to work with Natura and the communities in the Amazon to see what else we can do together. You're working with another 50-some communities out there, so there is an opportunity to scale what we've learned. We already partner with Natura on a larger scale in their operations; that's how we got to know each other. We've been doing this for 15 years with oil extraction. Now we're getting into the depth of your origins in recipe, R&D, supply chain. So there's also something around helping with the R&D center, innovation perspective, new recipes where similar logic can apply. We can tap into the richness of the Amazonian forest to replicate in different places. So there are many ways to scale up. Are there any plans to apply these lessons learned elsewhere? What's next for us?

J

Judith Visa3:51:58

You're talking question to me now. I think we also have some other nice examples of how our technology can help. On display we have nanofactories where you can containerize a mini factory and bring it to the Amazon. This could be multiple use cases to do something very locally by the same principles. We've been working with an institution and an NGO to help protect seedlings for reforestation. We decreased mortality from almost 40% down to 2%. We've used UV technology and visual inspection to detect contamination of nuts. So there are a variety of areas where the same principles could apply. Natura is working so well with this triangle. This could apply to different places. We've also been in the business of education. In Brazil we work with the Siemens Foundation and local institutions to ensure education remains part of what we bring to the country and ecosystem. There's a lot we can contribute as Siemens. Pablo said we have 28 use cases here for Brazil on this booth. So there's a lot to look at and unlimited opportunity going forward.

S

Studio Host3:54:02

Wonderful. Any plans from your side in regards of leveraging this knowledge?

J

Jeremian Love3:54:07

Yes. Well I think you've already mentioned some exciting things we are brewing at Natura. The innovation center is very exciting, something we want to expand. We're happy to do that in partnership with others, and importantly it's designed to be open. We have a vision of creating the Silicon Valley for the sociobioeconomy in the region. That's an important part of where we want to help this grow. The other thing is expanding these agro-industries, these nanofactories you mentioned. We want to bring more of this into the Amazon, with the view that this helps the communities and indigenous peoples capture more value so they can keep that and have agency. That's an important underpinning force. We talk about Industry 4.0, but I am so excited about what Amazon 4.0 looks like when we bring together these different technologies with the intelligence and wisdom that exists in these communities.

S

Studio Host3:55:12

Wonderful. And Judith you mentioned this morning in the other panel the VR goggles which you actually wear and you can look into the Amazon region and also smell it. So have you tried that already?

J

Judith Visa3:55:25

I'm going immediately after this panel, but I'm lucky that I've actually been into the communities. I've visited in person some of the things that journey takes you on. So I am absolutely going to go visit, but I would also encourage anyone interested in this concept of the sociobioeconomy to find ways to experience it, to immerse themselves in it. That experience is a great way to start.

S

Studio Host3:55:47

I just thought if you get homesick you want to go there maybe and cure that problem. Okay, thank you much ladies for the insights. Great story. Great products which are being produced. So definitely see for yourself if you want to put your nose in the bag to smell the Amazon maracuja, passion fruit, acai, the nuts. It's like you go on a travel itself. So thank you so much Judith and Chian for those stories. Awesome.

P

Presenter3:56:32

So let me start with a question. Is it actually possible to play a drum solo without any drums? Sounds impossible, right? Rhythm without impact, performance without energy. This feeling of 'this isn't possible' is exactly where innovation begins. So let's do a small check. What you see before you is two sticks. What I see is a full-fledged drum kit, snare, toms. Deep bass. There's the crash. And now for the easy part. Enjoy the rhythm of innovation. Heat. Hey, Heat. Impossible. So, but that's not even the best part. The best part is this one. We do something even more impressive and even more cool. We remove the short circuit current from a short circuit fault. How does this take place? This is due to our ultra-fast semiconductor switching technology in a breakthrough innovative device, the Siemens Sentron electronic circuit protection device, aka ECPD. Let me show you how this works. You have a short circuit. It comes through the mechanical contactors. There's a trip coil. It recognizes this. The contacts then open because this copper wire gets triggered. The only thing that has been protecting us for the last 100 years is a small piece of copper wire. The arc flows through the arcing chamber and gets extinguished, all in an impressive few milliseconds. Right? But look at that current: 4,500 amps. Now enter the Siemens Sentron ECPD. What happens here? We've removed the complete mechanics. We brought in the electronics. You have an intelligent microcontroller. The same short circuit fault takes place. The maximum current is detected. Immediate tripping due to our intelligent algorithms. We have freewheeling diodes. We've removed the arc chamber. Look at that time: 50 microseconds. So we're talking about a paradigm shift in electrical circuit protection. For the last 100 years it was a race of the short circuit current against the tripping mechanism. With the Sentron ECPD, we react in microseconds, and that's disruptive. Traditional protection reacts after a fault takes place, but the Sentron ECPD acts before the damage occurs. One major pain point in modern installations is inrush currents. This big LED panel behind me, when it starts up, has high starting currents. The protective device would trip. That's what it does. That simple copper wire thinks it's a fault. But these power supplies and capacitive loads need an intelligent circuit protection device. So we detect intelligently if it's an inrush current or a short circuit fault. What do people do? They protect the protector. They overdimension the circuit. But that's not how protection should work. With the ECPD, we detect, let it flow, and keep the power on when it needs to be. So instead of protecting equipment, we protect the application. The advantages: intelligent handling of inrush currents eliminates false tripping. Fewer trips, longer equipment life, higher availability, simpler planning. But speed alone isn't enough. Real value comes when speed meets intelligence. From intelligent functions to functional integration, we reach a new level of protection with the Sentron ECPD. It combines protection, monitoring, measurement, and control. We do AI too, all-in-one, intelligent. Functions are activated when you need them, not when the application forces you. Traditionally, protecting a building or installation would require many devices across the whole scale. Each device is a point of failure. With the Sentron ECPD, we help you keep it simple in the installation. Less complexity, less wiring, more space. One device instead of ten, a fraction of the weight. Real sustainability benefits. Sustainability by design, not an afterthought. This is what we at Siemens call innovation with purpose and responsibility, making the planet a better place for future generations. You might think all this is blah blah, but real impact is when we solve customers' biggest challenges. Take high frequency trading: milliseconds matter. A single power distribution can mean massive financial loss. With the ECPD, each workstation is selectively protected. A fault stays local. No cascade, no blackout. After testing, the customer told us the ECPD was the only solution that delivered total selectivity. Now let's move to the entertainment world. The same challenges appear in big football stadiums. LED boards were tripping breakers at every switch on. With the ECPD, we handle inrush currents intelligently. That means this Bundesliga team can focus on scoring goals while we keep their protection safe. Once protection is stable, customers ask for data transparency and control. Innovative customers need innovative solutions. You can find one of these interactive glass floors at the innovation hub, the last station on the left. We protect these LED glass floors from tripping main circuit breakers and enable measurement and adaptability. Protection becomes an enabler, not a limitation. Finally, a very interesting use case across industries. The theme is always the same: availability, reliability, intelligence. With our partner Blue Game in Italy, we are powering the next generation sustainable marine innovation on luxury yachts. Operators need to see the whole picture. We integrated the ECPD into the Gien navigation board so the boat operator can control the boat on the high seas without running down every time a circuit breaker trips. This is complete protection, monitoring, and remote control, letting the boat operator focus on the high seas while we focus on his protection. So when impossible becomes innovation, the ECPD is defining the future of electrical circuit protection. We are breaking the limits of what you think traditional circuit protection is. It's all you need and more. With our ECPD single-phase, we have more protection with residual current monitoring. And we have more power with the ECPD three-phase. Don't miss the chance to visit us at booth 173. We are waiting to hear your problems and challenges, ready to solve them with one of the most disruptive and innovative devices, the ECPD. So the next time you're at a music concert and it's time for that drum solo, remember the ECPD is all you need and more. You've been a great audience. Thank you for listening and wish you a wonderful Hannover Messe 2026.

C

Christina4:08:21

Welcome to Hannover Messe back.

Let's take a seat on the sofa of wisdom.

Oh my. Yeah, that's how we call it because it's always smart and clever people who know how to innovate, who know how to use the right technology.

Here we go.

Great you're taking the time to dive a bit deeper in our joint activities. Why don't you just quickly introduce yourself so our audience here knows who's who and which fields you are in?

R

Rob Smith4:08:51

Thanks, Christina. My name is Rob Smith. I'm the CEO at Keon, the supply chain solutions company.

C

Christina Vagner4:08:58

Hi together. My name is Christina Vagner. I'm CTO, Chief Technology Officer and Chief Digital Officer at OHB, which is a space company.

P

Peter4:09:08

Very good. And as you can see on the screen, so well done, my name is Peter and I'm looking after technology at Siemens.

C

Christina4:09:17

And strategy and a lot more and many more. Yes, and you brought this round here together Peter. At first glance it's quite an unusual combination of companies. We got Siemens as a strong leading tech company. We got Keon a champion in supply chain and logistics. And then we go on space and aerospace. We got OHB a pioneer of space and technology. What brings you together? Well, for one, these are great partners, and we're going to get there in a second. It's all about trust. We know each other for a longer time. So we together want to master the big challenges all of us are facing. No matter if you are Keon, OHB, or Siemens, we all have the same challenges. Geopolitics is a big issue right now. Everybody is facing uncertainties in the supply chain. Nobody knows what's going to happen. Then we have demographic change. We don't find enough people. Skilled labor is a massive shortage. There's the quest for being more resilient and more resourceful when it comes to sustainability and energy efficiency. So we all face the same challenges. What we said clearly is we have to address those challenges with technology. We got to solve it by being not working harder but by being smarter, by having access to all the data and knowledge that is out there. This is what unites us. We want to be successful in our respective industries and we want to do this smarter. That's a great approach, but that's probably much easier said than done. But let's dive deeper into the topic now. Christina, I'm focusing on you now. Where do you see industrial AI having the biggest impact in industry?

C

Christina Vagner4:11:17

So look, for us at OHB, industrial AI is a catalyst for two major areas. The first is accelerating the engineering lifecycle, and the second is strengthening mission operations. Our satellite and space systems, especially constellations, are getting more complex, yet the request is to deliver much faster than ever. Past development times that once took many years are now requested to be solved super quickly. As Peter mentioned, this is not purely from an economic point of view. There are geopolitical interests we need to master. AI helps us condense engineering cycles. For instance, engineering changes that took weeks are now condensed to days, sometimes hours. With digitalization, we improve traceability, reduce efforts in simulation and testing, and reduce human error. That is critical because time is not only an economic factor but also a matter of technological sovereignty. Once the satellite is deployed to orbit, AI comes in again to operate mission control autonomously and to find anomalies. We clearly see that the future in space is AI-driven and software-defined. In short, AI helps us develop faster, operate more securely, and stay ahead of time.

C

Christina4:13:52

Mhm.

And maybe because space is a super document-heavy industry by nature. Let me end with a lighter note. There used to be a joke that if NASA had printed all the Apollo documents and stacked them, you could build stairs to the moon. I'm convinced that with Artemis, you would need high-speed escalators. It is AI that helps us keep moving through the sheer complexity and volume fast enough. Okay, nice example. I'm pretty glad there is a lot of AI involved already in sending satellites up there. But you definitely need to have trust that what you have accomplished is safe. Now Rob, let me come to you. Where there are challenges, there are also opportunities. Where do you see the greatest of both in regards of industrial AI helping address at Keon?

R

Rob Smith4:15:05

Oh, thank you, Christina. Let me start by saying how excited I am we're announcing our Siemens and Keon partnership here. A strategic partnership connecting the real world and the digital world, bringing that together in physical and digital twins is a very exciting solution to some significant challenges in the supply chain. By design, everything is always in motion in the supply chain, things are always changing. Today's supply chains are more complex and vulnerable than ever. To make them future-proof, we need to make them resilient and flexible. This means designing optionality and agility, and being able to operate and optimize in real time. The answer is a digital twin. Bringing a physical twin and a digital twin to work together so you can design the next supply chain node in the digital twin. All the mechatronics, software, you can simulate, emulate, validate before building. The digital twin becomes the blueprint to construct the physical twin, then becomes the brain that operates the physical twin, thinking faster than real time, instructing all actors in the supply chain: people, humans, humanoids, robots, AMRs, automation, what's the next optimal step. That's what physical AI, industrial AI can do for the supply chain. That's what we're doing. We have an autonomous truck running in a full large-scale 3PL facility, recognizing what's going on, running logistical missions, operating safely amongst humans and other machines. With the work on the solutioning suite, we'll bring that large scale across the supply chain.

C

Christina4:17:16

Wow. So, you're thinking of a fleet.

R

Rob Smith4:17:19

I'm talking about in all the four walls and up and down the four walls, the whole supply chain being optimized all the time with digital twins.

C

Christina4:17:28

Wow. Very visionary. You definitely sound like you take it serious to be a good companion with the digital twin. That's for sure. Now Peter, all of that sounds promising. So what is still holding industrial AI back from scaling faster?

P

Peter4:17:47

Yeah. So first off, we love partners that have really big challenges and big dreams and aspirations, as Christina and Rob both indicated. Building something in space, revolutionizing the supply chain. What you need for that is intelligence, being smarter. It's the data. This is why the session this year is about how to build data ecosystems. The big difference to all the discussions on GenAI and large language models is that while we have large language models for consumers, based on language found on the internet, in industry, can you imagine OHB going out and publishing their latest satellite design on the internet? Certainly not. Rob wouldn't do that either. So the big difference in industry is the data challenge: how to collect data from production, engineering, design, and build the next generation frontier models for the physical world. The only way is by building open data ecosystems. That's why it's great to have Rob and Christina here, where we have partnerships to exchange data, each bringing domain expertise and the right data. Siemens can help bring this together, encapsulate knowledge into models that can be scaled universally. None of us can do it alone.

C

Christina4:19:49

Nobody. Siemens can't. Yes, we produce trains, substations, but we don't have enough data. OHB doesn't have enough data, Keon doesn't have enough data. But together we're getting there. In addition, we can apply all the great AI experts, build a model, make sure no IP is violated. That's the key. Then start to scale. That's the only way. Seems like you have a clear path. We're honored that Keon definitely joined this data partnership with us. How come you decided to join so early? I mean, this is not a test phase, but you're always in pole position when it comes to new technologies. Or was it because of Siemens as a trusted partner?

R

Rob Smith4:20:43

Thank you. There's a lot of trust involved and a common vision. A shared vision of connecting the digital and physical world and bringing AI into industry using the industrial foundation model. Our view is that accelerates engineering design, implementation, manufacturing. Great industrial companies need a great foundation: data. You need great data, but your company doesn't have all the data. When you can partner with companies you trust that see the same vision, it makes a very exciting first-mover advantage for our company and industry.

C

Christina4:21:41

Whole position for Keon here. Definitely. Now Christina, thinking of OHB and aerospace, it's highly sensitive data which you definitely don't want to unveil if you don't know to whom. What made this data collaboration worth pursuing and why did you choose to go with Siemens?

C

Christina Vagner4:22:05

So for sure there is a certain urgency for us currently because time to orbit is the new KPI we need to deliver on. This can only be done with excellent technology and tooling in engineering and production. You mentioned the sensitivity of data. I believe space data is one of the most sensitive industrial data because it's mission critical, security relevant, and highly proprietary. This is a challenging mix. A partnership needs to guarantee from the beginning a very high bar when it comes to trust, protection, and governance. That is why we chose to join very early: we want to be part of shaping the rules, not only follow them. I believe that if Europe with a company like Siemens wants to lead in industrial AI, it's also companies like ours that help shape those operating rules.

C

Christina4:23:33

Mhm.

C

Christina Vagner4:23:34

For us it was pretty natural to choose Siemens. There are certain key drivers. First, by design it's a trusted solution and platform because the data is sovereign and protected. Second, Siemens has the appropriate domain expertise; they understand how complex engineering, verification, and operation works for critical systems. Third, we see the huge potential of this bright ecosystem where space can participate from information across industries, sometimes industries innovating faster than us. Last but not least, and maybe the strongest argument, is the cultural fit: high expectation on quality and the heritage of engineering excellence makes the collaboration natural.

C

Christina4:24:58

That sounds great. Definitely Siemens knows how to innovate since 176 years. We have good expertise and passionate people working on that. Now, Peter, if collaborations like this are so successful, what is the avenue of the future going to look like? Where are we going to be taken to?

P

Peter4:25:19

Yeah, there's this great quote that says the future's already there, it's just unevenly distributed. I think Christina and Rob both will bring the future here and make it uneven. They have in their respective industries an unfair advantage because they moved early. What we are showing here at Hannover Messe is the first that you can see where this is going to take us. It's the IGEN engineering agent, which helps industrial automation scale faster because you have to program them, and today you don't find the programmers anymore. So we can significantly accelerate that in terms of quality and time. This is where industrial AI comes into play, where we can show it's trustworthy, secure, reliable. Now we just optimize this one step of programming a machine. But then we said, well, then it's piecemeal. You have all these many steps from designing a satellite or a forklift or an AMR. But what we want to do is the design, engineering, production, operations, maintenance, what we call the digital thread, so that you can optimize it with one shot and really make that work.

S

Studio Host4:26:46

Is what Rob was already alluding to is what we call the industrial foundation model.

R

Rob4:26:50

So the industrial foundation model thinks about end to end, considering engineering, design, material properties, layout, and manufacturing simultaneously to optimize in one shot. This is critical because you need all data from engineering, manufacturing, and operations. In Europe we have a big advantage in domain knowledge. By bringing that together with great partners like Keon and OB, we can scale faster.

S

Studio Host4:27:47

Great vision that becomes reality. What are your expectations for the next few months, Rob?

R

Rob4:28:20

It's like Peter talking about the future being unevenly distributed. Part of it is right now. Through our partnership with Nvidia, we've learned to get on an innovation cycle every two or three months, accelerating innovation to bring value to customers faster. It's a rapid cycle and we're all running fast on that treadmill together.

S

Studio Host4:29:21

As long as we keep the fitness program, we'll be up for the challenges ahead.

R

Rob4:29:27

Right.

S

Studio Host4:29:27

Christina, one more thing. You represent aerospace. Have you visited hall 26 and what ideas do you take home?

C

Christine4:29:55

Definitely. We all face similar challenges. It's fundamental to have systems designed for flexibility, software-defined, and AI-capable. This is an innovation leap for space and aerospace companies to master.

S

Studio Host4:31:04

Thank you. Great insights. We have gifts from our customer Natura. Enjoy the fair.

C

Christine4:31:57

Thank you.

S

Studio Host4:32:10

Hi. How are you two doing?

C

Christian4:32:14

Pretty good.

C

Cal4:32:14

Pretty good.

S

Studio Host4:32:18

Christian, tell us about yourself.

C

Christian4:32:23

I work at RWTH Aachen, responsible for machine tool automation, robotics, and gear technology, and head of the Fraunhofer Institute for Production Technology.

S

Studio Host4:32:37

Cal, what do you do at Siemens?

C

Cal4:32:42

I lead research and pre-development, a global team of 1,200 people in seven countries working on Siemens technologies.

S

Studio Host4:32:57

Christian, how has academia's role changed regarding industrial innovation?

C

Christian4:33:28

We always ask about relevance of our research and how to transfer to industry. About 30-40% of our budget goes into industrial contacts.

S

Studio Host4:34:01

Cal, why is it important for Siemens to work closely with universities?

C

Cal4:34:12

Universities are a technology radar, looking ahead. They do foundational research we can't. Collaborating on existing topics and the validation cycle is extremely valuable.

S

Studio Host4:35:10

How do these projects help real production processes?

C

Cal4:35:32

We start with an idea, develop a proof of concept, then create a market solution. One example is the Run My Robot Direct Control project with Christian's team, enabling robots with direct measurement for machining. It's in the market today.

S

Studio Host4:36:39

Christian, from your perspective since 2011?

C

Christian4:36:42

We need access to real data from machine tools. Collaboration with Siemens opened the door to get data that is normally hard to get from customers.

S

Studio Host4:37:15

How are data spaces and alliances transforming industry?

C

Christian4:37:40

Data alliances are important because of sensitive data. We need a neutral platform where companies can share data safely. Standardization is critical for Industry 4.0.

S

Studio Host4:38:24

Do you agree, Cal?

C

Cal4:38:25

Absolutely. Data is a strategic asset and must be sovereign. The Factory X project with Christian's team created a neutral platform for data sharing across the value chain.

S

Studio Host4:39:16

Cal, how do you see academia-industry collaboration for physical AI?

C

Cal4:39:41

Very significant. Many physical AI technologies originated from universities: vision-language-action models, reinforcement learning, domain randomization. The innovation cycle is rapid because of this collaboration. Our innovation hub shows robots in action using these technologies.

S

Studio Host4:40:52

Christian, do you agree the optimization cycle is increasing?

C

Christian4:40:58

Yes. Under Industry 4.0, we use AI and human intelligence. We work on large language models for physical systems, perfect for fundamental research and direct industry transfer.

S

Studio Host4:41:45

Human in the loop. Christian, thoughts on humanoids?

C

Christian4:42:11

Huge potential. Many industrial places are designed for humans, so humanoids could substitute in the midterm. But we must consider safety. I'm convinced they will be in the near future.

S

Studio Host4:42:50

Cal, can you calm people worried about humanoids?

C

Cal4:43:06

Humanoids are extremely complex, more than electric cars. We use a cognition layer with probabilistic intelligence and a safety layer with guard rails. Safety is a principal component from the start.

S

Studio Host4:44:30

Where can people learn more?

C

Cal4:44:40

At the innovation hub, we show our work with cobots and humanoids.

S

Studio Host4:44:56

Takeaway from industry-university collaboration? Cal first.

C

Cal4:45:01

The shortest way from idea to impact goes through collaboration, and university is the best partner.

S

Studio Host4:45:10

Christian?

C

Christian4:45:11

Strategic alliances bring fundamental research directly into industrial applications. This alliance with Siemens has lasted decades.

S

Studio Host4:45:26

Thank you. Applause for Christian and Cal. Gifts from Natura.

C

Christian4:45:48

Thank you. Have a great fair.

C

Cal4:45:52

Thank you. Bye.

S

Studio Host4:46:08

Let's take a seat on the sofa of wisdom. How are you doing?

D

Daniel Klene4:46:13

Great. Thank you very much.

S

Studio Host4:46:15

Quick who's who. Daniel Klene, VP Consulting at Siemens. You're the crisp tester?

D

Daniel Klene4:46:34

I've become an expert.

S

Studio Host4:46:36

Ronnie Matis, plant director at Pringles.

R

Ronnie Matis4:46:41

That is correct.

S

Studio Host4:46:42

He ensures tubes are filled correctly.

R

Ronnie Matis4:46:47

Correct.

S

Studio Host4:46:47

Yan Lannon, global digitalization lead at Pringles.

Y

Yan Lannon4:46:53

Correct. I let the digital twins dance.

C

Cedrik Neike4:46:59

I'm the key customer.

S

Studio Host4:47:02

You're the key customer. And this gentleman won the crunch experience this morning.

R

Ronnie Matis4:47:09

We had a kickoff: who can make the crisp crunch the most? I won. 50 years of training.

S

Studio Host4:47:23

Cedric, member of the management board and CEO Digital Industries. Now Cedric, what global trends are you seeing in CPG?

C

Cedrik Neike4:47:50

I love food. CPG is a 2.5-3 trillion dollar industry, not consolidated, with huge technology needs for quality, taste, sustainability. 75% of food comes from 15 plants and 5 animals. We need to ensure sustainability. That's why we highlight Pringles as a key example.

S

Studio Host4:49:13

Ronnie, add something?

R

Ronnie Matis4:49:21

The real challenge is variability. At scale, small variations impact thousands. Historically reactive. With Siemens, we built a digital twin to see dough behavior in real time and guide the process before it happens. That's real transformation, making people and technology work together.

S

Studio Host4:50:53

What was the situation before?

R

Ronnie Matis4:50:58

Quite challenging. Demand exceeded capacity, processes unstable, high waste. Core problem is variation from natural products. Relied on people, not scalable. Turning point was partnership with Siemens in 2023.

S

Studio Host4:52:03

Daniel, what were your goals?

D

Daniel Klene4:52:18

We assessed the factory, identified 14 initiatives, focused on three: digital twin, AI process control, energy management, predictive maintenance. For AI, we used 'death criteria' to evaluate after 3 months. Ronnie accepted.

R

Ronnie Matis4:54:08

I accepted those criteria. It said a lot about our journey.

S

Studio Host4:54:22

This was a partnership, not just supplier-customer.

Yan, how do you scale from Kutno globally?

Y

Yan Lannon4:54:59

We proved it on one line by 2025. Now scaling to US and Belgium factories. We also are reapplying models to other food platforms and connecting manufacturing with R&D through digital threads, enabling infinite learning cycles.

S

Studio Host4:57:37

Cedric, what becomes possible with full connectivity?

C

Cedrik Neike4:57:51

Infinite learning and experimentation. You can launch products in days, shift globally, save energy (7% per chip, huge overall), adapt to supply chain changes. Most companies have too many pilots. You need continuous thinking through the digital thread.

S

Studio Host4:59:52

Daniel, how does this vision come true?

D

Daniel Klene4:59:55

Pringles started with a business challenge. The data pool from the digital twin was reused by R&D and procurement. Then we added plant simulation. Each step builds the industrial metaverse.

S

Studio Host5:02:09

Yan, how do you scale this globally?

Y

Yan Lannon5:02:45

We reflect on business needs. For food and beverage, driving digitalization in supply chain delivers productivity and innovation. Critically, we need to bring people along, creating a data-first culture.

S

Studio Host5:04:46

Quick summary. Ronnie?

R

Ronnie Matis5:05:02

It was a big risk, but we dared to dream big. Now people spend less time firefighting, take data-driven decisions, and have confidence. The transformation is real.

S

Studio Host5:05:56

Cedric, first thought?

C

Cedrik Neike5:06:02

Great taste does not produce big waste. If we work together, we can produce faster, better, more sustainably. High-tech minds in this industry is a pleasure.

S

Studio Host5:06:27

Daniel, how often do you call?

D

Daniel Klene5:06:38

Depends on the week. We have a regular call every Friday, meeting a couple times a week.

S

Studio Host5:06:57

Thank you to all. Big round of applause to the four musketeers.

With this we conclude. Think of this story wherever you go. Favorite flavor? Salt and vinegar for me. Thank you.

Isn't it cool we're dressed alike?

C

Cedrik Neike5:08:40

Yes. This is what happens when you share confidential information. Be aware.

S

Studio Host5:08:46

A pleasure to welcome Kristoff Ban from Microsoft. Kristoff, VP engineering and UFO.

K

Kristoff Ban5:09:03

Thanks.

S

Studio Host5:09:06

I had an ex-file moment with UFO. Take a seat. What has to change in cybersecurity?

K

Kristoff Ban5:09:57

We are in the fifth industrial revolution. Cybersecurity will play a key role because exposure and velocity are unmatched. You can also leverage AI in cybersecurity to help with other AI workloads. Using secure agents will change the game.

S

Studio Host5:11:01

Natalyia, how do we use threats as opportunity?

N

Natalyia5:11:07

Speed is key. AI gives opportunities like quick robot configuration and use of glasses. But if data confidentiality or integrity is compromised, there are dangers for humans cooperating with robots and factory availability. That is worse.

N

Natalia5:12:16

We're going to have a tire that is not done with the right quality. And those are exactly the risks that we have and that we are facing because of AI, which is wonderful opportunities. We don't want to stop that, but we need to do cyber security move faster and deploy it. I think the work here, Melissa, is real time. Real time. And we talk about this Christoph patching. We cannot wait 12 months to patch something in the factory. Talk about this because I found his point of view.

M

Melissa5:12:54

We can talk a lot, but now I'd like to know, you know, many leaders are looking at cyber security as something that is actually slowing you down. So, in practice, what does that look like? And when cyber security actually becomes the foundation and not something that is stopping us down but rather speeds us up.

K

Kristoff5:13:15

So if you think that cyber security slows you down, I will be very transparent with you: then you're doing it wrong. Because at the end of the day, cyber security helps you to actually accelerate. It helps you to measure risk, to really identify the risk vectors and how to think about these things. When people thought about cyber security as an anchor, it was all about the wrong tooling, the wrong process, the wrong approach, or a legacy approach into a software world that is ultimately not adequate any longer. So the way to think about it, and exactly to your point, is like everything is speeding up. In the past, when a vulnerability came out, people thought they had 12 months to patch it. You don't have those 12 months because in 12 months you are already shut down due to exposure. How can you help with that? You also use AI to accelerate the tooling behind it, so you don't have to have humans any longer doing testing and validation and human-based processes. You also do threat assessment management and all of those things in a way that will accelerate whether you like it or not.

M

Melissa5:14:36

It will accelerate whether you like it or not.

N

Natalia5:14:39

And if you embrace a new software-defined pattern also for cyber security, then you actually start to see how that can work hand in hand and accelerate your business process quite honestly. How about your perspective? I want to talk on top of what Kristoff had said because he's the VP for engineering at Microsoft. One of the key aspects you need to do in cyber security is to deploy cyber security by default. The word is shift left. What we do is include in the tool chain of the engineering, the tool suite that you use to develop products, to include cyber security. I think Kristoff can tell us a lot about this.

M

Melissa5:15:27

Before I go with Kristoff, that brings me to the next topic that I think is key. We need to cooperate.

N

Natalia5:15:37

Yes. For us to cooperate is not about sitting together, drinking coffee and talking about the last incident we had, but about sharing data. In this case, Siemens and Microsoft have very good contracts so that we can share that and speed up the protection of our products and of our customers. Kristoff, maybe you can tell something about that training in engineering.

K

Kristoff5:16:10

The way I always describe it, and exactly to your point, it is a shared responsibility. Ultimately, cyber security, software supply chain risk, all of those things are about sharing the responsibility and ownership and accountability. The way Siemens and Microsoft work together is we have our core competencies. We are really good in some areas, Siemens is good in other areas, but you need both areas working very well together to get a grip on this new threat world. When you think about this very heterogeneous environment that customers are always in, it is never only Siemens, never only Microsoft, never always Google or AWS or Schneider. It is a complex, complicated world. So bringing our core competencies together and leading this together is really about acceleration. When you ask me about AI, it is all about acceleration at the end of the day.

M

Melissa5:17:15

Let's talk about risks now. When AI starts scaling across factories, bigger risks can occur. The surface is larger than we can expect. But how do we track what's happening? Everyone starts using their own tools. So much can happen. So how do these partnerships and initiatives like Charter of Trust help to continue?

N

Natalia5:17:40

AI is a risk, but also a huge opportunity. Kristoff and I were talking before the conversation today about these new AI models that give us the opportunity to find vulnerabilities quicker. From the testing that Microsoft is doing, we know that you can compress one year of pentesting into weeks. That's a big opportunity. This is where Charter of Trust comes in place because we have a partnership together and we have this commitment of protecting the digital world by creating trust. In this partnership, we share not only data but we act to protect the ecosystems where we coexist. Kristoff mentioned already, it's not Siemens purely, not Microsoft purely, it's everyone together in environments of customers like...

M

Melissa5:18:49

You name it. I just failed to mention one of them. So yeah, this is what I rounded off. You saying we hack into our system first?

K

Kristoff5:19:01

And that gives us the security and the strength to avoid those kinds of risks. What are you saying? Well, the short answer is yes. The way Microsoft and Siemens work together is that we ultimately embrace the new pattern, the shift left, the tool chain approach to look at our own solutions, learn from each other, share. To reflect a bit more on your question as to AI introducing risk, I will be very transparent with you. It doesn't; it just accelerates the risk that we always had in the first place. We just didn't know.

M

Melissa5:19:34

Yeah.

K

Kristoff5:19:34

It's all of those things. Ultimately, AI by itself is just a way faster business process implementation of the things that we had. Quite honestly, the past attitude of ignorance is bliss may have worked for a long time, but it definitely doesn't work any longer.

M

Melissa5:19:53

Love that.

So let's become concrete. I want the nitty-gritty, tangible, real stuff. Is there one situation where having the right security in place helped us move faster or helped us implement when it comes to AI to get better outcomes?

N

Natalia5:20:10

It's clear, and you can read that in many studies. If you do that by default at the beginning of the development, then cyber security is going to cost cents compared to what it costs if you forget to deploy it at the beginning and have to deploy it at the end. It's very easy: you have to stop productive systems from running to apply security if you haven't done that at the beginning. Applying it at the beginning will save you not only a lot of time and headaches but a lot of money. That doesn't include the fact that if you don't include cyber security, the possibilities for an attack are high. You will get that. If you don't apply cyber security, you are very much into getting damage: stopping your factory, ruining your reputation. We have seen a lot of these cases in the news.

K

Kristoff5:21:21

And of course, we have to be honest with you with the current political situation. This is increasing state-sponsored attacks, increasing the motivation to attack critical infrastructure. We coexist as Microsoft, as Siemens, as AWS, you name it. We coexist in the critical infrastructure.

M

Melissa5:21:47

Yeah.

I'm thinking the same for you. You probably have an example for us.

K

Kristoff5:21:51

Sure. We have many examples because it happens every day.

M

Melissa5:21:54

Well, I want one. We have four minutes.

K

Kristoff5:21:56

Let me tell you about the story now. Let me give you two very specific examples. One more of a root cause and the other one, how do we mitigate? As you can imagine, Microsoft in these days, we are all into data center business. Data centers are the factories of the future. It is not the fancy GPUs, it is all about OT, energy management, risk vectors, massive scale operations. Others call it factories, we call it data centers. And so we are exposed to this like everyone else. We partner with Siemens to bring our expertise into the infrastructure with regards to scale, and have Siemens help us with automation, energy management, cooling. This is a first-party example of how we work together. Another aspect: when you take our joint customers, every customer that Microsoft has is also a Siemens customer. The way we think about these things and go to customers is that we integrate solutions with each other because you don't have these silos any longer. Siemens has incredible process engineering offerings, automation when you talk about virtual PLCs and all the new stuff, but you have to run it somewhere, secure it. There is security from an OT point of view and from an IT point of view, observability. So we come in and say, ultimately, Siemens' product portfolio is amazing if it runs on Azure. Our cloud offering takes it up a notch even further because they work together. This is how we recommend customers think about it. It is not an either/or, it is an and. That's important because it accelerates you.

M

Melissa5:24:01

So all that you've said, I'm taking with me that it's about partnerships. We need to talk to each other and partner to make this happen. Last two minutes, last question. Looking ahead, what has to change in organizations to really work together to make industrial AI both secure and scalable?

N

Natalia5:24:26

I will take two things. The number one thing is speed, real-time protection. I want to be more explicit and take what he told me minutes before the conversation because I think it's very important. The times when you could wait 12 months or whatever amount of time until your next maintenance window in your factories, in your industry, in your warehouses, those times are gone. You need to push that real time immediately and let AI help you do that. I love those words from Kristoff. I definitely take it for me and I hope for the audience as well.

K

Kristoff5:25:17

If I add on to this, I completely agree with you. If you really look at AI in this entire context, AI gives you a lot of luxury. It gives you faster business processes, changes the way you think about your business. It gives you benefit to be faster, better, brighter. But the same tooling is available to the bad guys. So as you think about your own world, instead of thinking about a particular process for several months, you now brought it down because we have the industrial co-pilot and AI tools. The same tooling is available for the bad nation-backed actor that wants to exploit what you have. So while you have this luxury, you suddenly gained a responsibility to not be complacent any longer, because complacency will be the thing that makes it or breaks it.

M

Melissa5:25:44

But the same tooling is available to the bad guys.

K

Kristoff5:25:48

So as you actually think about your own world, it's like, instead of me thinking about a particular process for several months, I now brought it down because we have the industrial co-pilot and AI tools. The same tooling is ultimately available for the bad nation-backed actor that just wants to exploit the things you have. So while you have this luxury, you suddenly gained a responsibility to not be complacent any longer, because complacency will be the thing that makes it or breaks it.

M

Melissa5:26:23

So if I may round that up, cyber security is what turns everything into what you can trust and scale. If we're talking about AI, speed, anything, it shouldn't be looked at as a showstopper or a barrier, but as an enabler.

K

Kristoff5:26:42

Yes.

M

Melissa5:26:42

So, thank you Natalia and Kristoff. This was an amazing session to learn about the importance of cyber security. But to be honest with you, I'm going to hand over to my colleague Christine because you know what we're going to talk about next? Autonomy, speed, and we're going to take it to the next level. Thank you everybody.

N

Natalia5:27:01

Melissa and Kristoff, thank you. Thank you very much.

K

Kristoff5:27:03

Thank you so much for the partnership.

M

Melissa5:27:04

Thank you.

C

Christine5:27:18

Now, the picture says it different, but I think you can match the who's who on the sofa of wisdom here. Going to do a quick introduction round. We got Rhina Brim. He's the COO of Automation Business and also the CTO of Digital Industry. So you're wearing two hats, Rhina. Which one is bigger or which one do you like better?

R

Rhina5:27:43

I mean, that use case needs both.

C

Christine5:27:47

Okay, that's a clear answer. And we got our partner here from Accenture, Vivek Koshik. You're the managing director and global head of Siemens' business group at Accenture. So you're fully focusing on the projects we are doing together.

V

Vivek5:28:03

100%. So I am 100% Siemens.

C

Christine5:28:06

That's great having you again. I said that before. You are a Siemens partner here on our stage and it's great that you are putting that importance into your presence here. Thank you for that. Rhina, I'm going to start with you. When we talk about the potential for our customers moving from automated production towards a more adaptive production, how is that done and why is it so important?

R

Rhina5:28:36

Well, you're right. In this use case we even go further because you say we want to go from automation to flexible and adaptive to autonomous. In that use case you're going to show here today, we are really already more into the autonomous than even on the flexible and adaptive. That's really great because it opens new areas for our customers in how they can run their operations. What you need for that is to navigate through a very complex environment. You cannot program everything anymore because things might change. That's why we go from hard-coded tasks into more goal-based automation. We tell the system what to do and the system knows itself how to operate it. This is a principle concept, and we see a use case here where this is already implemented. It's not only a vision, it gets reality.

C

Christine5:29:33

And that's my question to you, Vivek. In regards to what's the current situation in pharmaceutical and chemical labs, and what are concrete benefits that autonomous production brings along?

V

Vivek5:29:44

Thanks, Christine and Rhina, for having me here. I'm excited to talk about our autonomous robots offering. The situation today: QC and analytical labs are manual with limited automation. Compared to our supply and factories, which have been industrialized a lot, labs are still dominated by manual work with data fragmentation and non-scalability. Labs are the bottleneck to business acceleration. How do Accenture and Siemens unblock the bottleneck? For our clients, for example BASF, we are bringing joint offerings together. We are creating digital twin and AI training models for the QC or analytical labs. With that, we are able to create trainings for robots so they can move autonomously on the material workflow. We are also training data models for the robots so they can work as a co-pilot with lab engineers, improving productivity and accuracy. That's how we turn labs from bottleneck to business accelerators.

C

Christine5:31:06

It sounds easy, but I'm pretty sure there is much more to this than just using a bit of data. Rhina, I'm going to ask you, you have a lot of experience in contact with customers. What would you like to add on what Vivek just stated?

R

Rhina5:31:20

Basically, this is what we also show here on the fair. We come later on. We say there's automation, and we added already since years certain skills to automation, like grasp it, do one thing, but it's only one skill. One skill is not good enough to fulfill applications in a lab. So you need to go from skills even to tasks. How we can automate entire tasks is what we see here in a practical use case.

C

Christine5:31:47

And which technologies stand behind all of this?

R

Rhina5:31:50

It's very much the topic as Vivek said: simulation, digital twin, photorealistic simulation because you need to create data. Then it's really physical AI because these robots need to be controlled. All the technologies you're talking about come to reality in that use case.

C

Christine5:32:13

Okay, sounds promising. We have achieved a lot, I would say. Now, Vivek, one year ago exactly, the Accenture Siemens business group was founded with the aim of helping clients reinvent their engineering and manufacturing. What's the concrete role of Accenture and Siemens in this example?

V

Vivek5:32:36

One year back we launched the business group here on this platform. A lot of clients ask us exactly what is the role. Is it just technology and system integration coming together? I thought about that a lot and I want to bring an analogy. I compare the partnership like a Formula 1 racing team. The purpose of Formula 1 is to win races. Clients are there to win their digital transformation race, to get ahead of the competition. In that race setup, you have technology, a car, which is Siemens in this game. But you can't win the race just with technology. You need a data and engineering team that picks up the software, technology, data, and AI to execute and make a strategy. That's where Accenture comes into play. Together, we are creating joint offerings. It's not just combining tech and SI, but really creating AI models for specific industry templates, assets, and accelerators with Siemens so that we can get a head start for clients when they run these projects.

C

Christine5:34:02

I wonder who is the driver then, who is in charge of training the driver? But move on. Rhina, it's not just a vision anymore. You mentioned the BASF topic, your joint pilot customer to bring this to life. Can you explain a bit deeper what was planned?

R

Rhina5:34:27

First of all, Accenture did a great job because there's a customer need. As Vivek said at the beginning, at BASF, the labs are the bottleneck of the entire flow of the factory. If you operate only with humans, they probably operate from Monday to Friday during working hours. But if you want to run a continuous process, the lab should work at night and on weekends. So how you come from a bottleneck to a topic where it will run and support the operation, going to more autonomous operation, is very important. It also needs business consulting to figure out how to do that. We convinced the customers that this makes sense and creates big value. With the pilot customer BASF, we go into a 9-month proof of concept. They need to be convinced, but we are very convinced. It not only runs here in theory; it runs also on the Accenture office shop floor. It's really running in life. We are providing a lot of technologies: standard PLC, digital twin, robot task execution, fleet manager, safety in a shared environment. We are taking the technology stack and bringing it to that use case with BASF. I'm very confident that this will have a big impact for the customer.

C

Christine5:36:21

Question to you, Vivek. Usually when Accenture comes in, you're speeding up processes. So how have you accelerated this project?

V

Vivek5:36:33

What we try to do is scalable and repeatable solutions. As Rhina just mentioned, we brought all the AMR with Siemens' C-Move technology into our Accenture Munich lab and recreated the whole lab scenario as if it's a BASF lab. We are creating the digital twin using Siemens' Technomatics platform and creating AI data models specific to the chemical industry. With that, we are going to create a head start for BASF on how to scale from one lab to 100 labs. We are creating test scenarios already in Accenture Labs using Siemens technology and coming with pre-configured solutions to clients.

C

Christine5:37:17

It sounds like you know what you have to do. Looking into the future, we had discussions on this sofa about AI. The future is not just a thing of one year or five years; it's really fast. If you think of the future like sitting here next year again, how would you say this is no longer a promising concept but a scalable model for the lab of the future?

V

Vivek5:37:46

I'll have three things. If I fast forward 12 months: number one, we talked about bottleneck. We need to unblock the bottleneck, turn labs from a bottleneck into a business accelerator. Number two, we talked about technology a lot, but we didn't talk about people. At Accenture, people are at the center of AI adoption and scaling. With these projects, we give opportunities for the client workforce, like BASF, to get trained on the latest skills and be future-ready for scalable projects. Number three, I would like to see BASF as the leader in the chemical industry to demonstrate how you transform labs into autonomous labs, making it from one shift to 24/7 to bring productivity, accuracy, and faster time to market.

C

Christine5:38:46

Great statement. As a closing runner from your side in 12 months.

R

Rhina5:38:52

First of all, I want in 12 months our client to be happy. For that, it needs to be reliable, run 24/7, which is a big task. At the end, that application is not specific to BASF; it's typical for chemical, pharmaceutical, or all kinds of lab automation. If we make that successful, I expect BASF to scale it at BASF, and we together then scale it beyond our lead customer.

C

Christine5:39:27

Sounds great. Times up. There's just one more question to you, Vivek. Where can we find you and Accenture at the fairgrounds?

V

Vivek5:39:34

We are in hall 27 right here, everywhere in Siemens.

C

Christine5:39:38

That's a good one. We have a great demo at manufacturing orchestration in innovation hub and Accenture booth hall 16.

Okay, wonderful. There are also colleagues who will be presenting a deep dive into the lab of the future with speakers from BASF, Siemens, and Accenture tomorrow at 10:15 on this main stage. As you mentioned, the showcase is something. I have a little something for your journey back. We always bring a gift to our speakers. This is produced in Brazil from our customer Natura with Siemens technology. Maybe we look into that process as well, maybe we can do even better and get more out of it. This is a bar.

V

Vivek5:40:29

Again today.

C

Christine5:40:31

Yes, you definitely will need giveaways when you come home. I know there are a lot of people working in your team, and they will be happy to get the flavor of the Amazonas.

Thank you so much. Big round of applause to the two of you.

R

Rhina5:40:45

Thank you.

V

Vivek5:40:46

Thank you.

C

Christine5:40:47

Great partnership. Looking forward to having you on stage again, Rhina. Thanks.

Let's take a seat on the sofa of wisdom. When we moved into hall 27, which is the first time that we are exhibiting here, we said we took the living room with us. Same setup. Everybody's happy. You're a happy group here. I'm going to do a quick introduction round. We got Linda Groomholds, global senior vice president, Siemens Accelerator. We got Rudy Bassau, our CFO at Digital Industries at Siemens. We got Dion Smith, worldwide responsible for the ecosystem at Siemens. And we got Frederick Jansen, CIO, Digital Industries. Great that you're taking the time. I know this is peak time for those on the sofa here because you have a busy schedule. Now, as I mentioned, customers expect a very simple, easy way, direct path from finding to buying. At Siemens, we made this already available with our C portal. Heavily used, very successful, customers are happy. We are now connecting this even further to create one seamless journey. I'm starting with you, Linda. How does the Siemens Accelerator now fit into this development?

L

Linda5:42:29

Actually quite nicely. Siemens Accelerator is our digital business platform which has a commerce portfolio, an ecosystem, and a marketplace. This fits nicely into the buying journey of a customer. There are customers who have a product ID in mind and want to search and buy. There are also customers who don't know us well, have a specific challenge, and want to see a solution, kind of an inspiration. In the B2C world, if you are invited to an event and have a challenge on what to wear, you don't necessarily know you want to wear orange clothes. You want inspiration. That's how Siemens Accelerator is in the B2B world. We curate the portfolio according to customer challenges and industry, showing the art of the possible across all portfolio lines: hardware, software, services, combined with ecosystem solutions. Customers can explore, educate, and finally purchase. The most important thing is that Siemens Accelerator marketplace sits on siemens.com. When you enter siemens.com, you find everything there, with one checkout process, one basket. We still have our very successful C portal. If you have a specific product ID, you can still go on C portal, which is fully integrated into this journey. That's also Rudy's role, fully integrated in all processes, knowing where we need money to support creating solutions. Now, from a business perspective, Rudy, why is digital sales so important and where do we stand today?

R

Rudy5:44:30

No, I think a CFO, it's in the interest of any company to scale revenue without scaling cost. Customers today are looking for simplicity. One checkout basket, one login ID. We as Siemens believe we can scale digital revenue without scaling cost. If we can standardize, you will see stronger product margins, but also get benefits like live sales transactions creating data points that can be analyzed for value. Where do we stand? It's fortunately not a vision. We have today more than a million digital registered users that are logged in with us. One million. More than a million. We have roughly 260,000 digital touch points where companies are reaching out to us, and we are transacting with roughly 150,000 customers electronically. Short message: digital sales makes life easier for our customers and for Siemens.

C

Christine5:45:45

Okay, that's great. And happily they're coming here to listen to us. Now, Dion, coming to you. Thousands of partners are working with Siemens every day. What makes these digital applications valuable to them?

D

Dion5:46:02

As Rudy just shared, we have 150,000 customers transacting digitally, and over 70,000 of those are partners. When we think of the partners' journey, time equals money, but for partners, money is margin. It's incredibly important for us with our partners that we are easy to do business with. Ease of doing business is fundamental. Most partners are not just transacting with one vendor; Siemens is one of maybe 10, 20, 100 other companies they work with. So our ability to work with partners via C-Sales, where they can configure, price, and buy, is a necessity for our success with partners. That digital backbone is critical. When we invert over to the marketplace, to Accelerator, many of our partners have already built innovative solutions on Siemens. And back to what Rudy and Linda shared, we get over a million visitors coming into our marketplace. This is a phenomenal shop window. For our partners to put their solutions into the Accelerator marketplace gives them greater reach and visibility into the market.

C

Christine5:47:35

Sounds very promising. I'm still astonished about the vast number of partners, clicks, and services you offer. So, Rick, from a technology perspective as the CIO, why do companies need platforms to enable these kinds of digital customer journeys?

F

Frederick5:47:55

Customers these days require, if not expect, an Amazon-like experience. They want to easily transact with us, which requires bringing different things together. A friction or not seamlessly integrated buying experience doesn't help. We want to help them find what they require, orientate themselves, finalize exploration, and then execute. The best way to do that is to bring it all together in one platform because there we have it under control. We can master the data, make sense of it, and guide customers in their buying experience to ultimately make it easy to transact with us.

C

Christine5:48:47

You say it's easy, but convincing someone to change a running system and go to a new one is probably quite complicated. Linda, how do the Siemens Accelerator marketplace and C portal complement each other in the overall digital journey?

L

Linda5:49:08

It's a seamless journey but two separate execution paths. On one hand, you have comprehensive solutions to explore on the Siemens Accelerator marketplace. We have 1,500 offerings from Siemens and another 900 from partners, solutions curated on this one. On the other hand, we have the C portal where we have configurations. 80% of customers are looking for a specific product ID and know C portal, so they can use it in the future. If you are on Siemens Accelerator marketplace on siemens.com and want to dive deeper into hardware, you can connect directly to C portal. The most important thing is that we are on a path to integrate this even further, with one customer ID going forward. When you enter with one login, one account, you see everything you are doing with us and with partners, independent of online or offline. This omni-channel experience, customer 360, is the most important thing. You still have connection to sales representatives in regions, connected into the digital world. One checkout, one basket, one customer ID, everything visible for us and for customers. Do we also check on the expectation of those customers, like how was your shopping experience? We do that in private, we also do that.

C

Christine5:50:59

Yeah. So there's always feedback kindly requested, but we are also using agents and analytics to understand the customer journey and improve further.

This is where AI and data comes in again, ladies and gentlemen. You kind of see me talking here where this pass goes to. So, Dion, when customers navigate complex industrial portfolios today, where do they actually struggle the most?

D

Dion5:51:29

Customers are really looking for confidence that what they're going to buy is actually going to work, deliver the outcomes they're solving for. If you think about being a consumer on Amazon, the first thing I do is click four stars up. I'm not looking to buy anything from one, two, or three stars. Four stars gives me confidence that it's proven. The beauty of the Accelerator marketplace with Linda and the team is they've done all that work. We don't put anything into our marketplace that hasn't been vetted, tested, understood. You asked about ratings. Are we there today? No. Is that where we expect to get to? Absolutely. We need that marketplace to be consumerized in the way we buy as individuals. From our perspective, being able to represent our partners' solutions in the marketplace and have validation from the Siemens brand is a huge confidence builder and accelerant. When customers come to make that purchase, they have that level of confidence. It will continue to mature. At the moment, we have many solutions, but as more customers buy those offerings via our partners, that will continue to build.

C

Christine5:53:25

I like that topic of trust in a certain brand. You definitely don't want to be disappointed, and you for sure want to have those five-star ratings we're working on. Rick, technology is evolving quickly. We see that here. We just talked about the future not being further away than six months. How does AI help to simplify digital customer journeys?

F

Frederick5:53:52

We talked about platforms before. That's the foundation to get started with AI, but AI can take the whole thing to the next level. Ideally, AI picks up the user or customer where they are, helps them navigate an increasingly complex portfolio. We have a lot of offerings on our marketplace and C portal. AI can support search, do recommendations, lead to the next best action, so we can help customers drive much smarter exploration of what we offer, then execute. Linda was talking about omni-channel experience in a B2B world. That's what customers require and expect from us. AI can help us guide them through different channels, capture rich insights of customer intent, and with that intent help them transact on our platforms. AI will help us be much faster in decision making, have a seamless experience, and ultimately drive value for our customers.

C

Christine5:55:12

And here we are, Rudy, asking you now: how do we at Siemens ensure that these digital solutions really deliver that expected value to our customers?

R

Rudy5:55:25

We have a simple rule at Siemens. We try first to be the customer zero, the guinea pig. We want to try it. As Rick was saying, the power is in the platform, but only if it works end to end. We test these platforms in our own businesses. If they work, great. We refer to it as drinking our own champagne. Sometimes, luckily not often, it doesn't work, and we call it eating our own dog food. Even if eating our own dog food, we are still happy because that means we could have prevented our customers from eating that dog food. We test until we get to a point of scale in Siemens. If we can scale in Siemens, that's a good trigger point to know we can scale with our customers. Last but not least, as we go live together with our customers, we learn from real actual transactions. Summarizing, it's about customer zero and then giving our customers the confidence to scale.

C

Christine5:56:38

Great insights. As a matter of fact, we have lots of customer showcases exhibited here at the fair booth with Gula, Gia, Pringles, Pepsico, Natura, and many more. There is also one very innovative showcase in our innovation hub, which is our Siemens electronics work in Amberg, where we have a production line. This is the fancy augmented vehicle Humanoïd showcase. Don't miss the chance to see what Siemens is providing to Siemens as a customer to realize great solutions which we then want to bring further. What we've seen here and heard from you is that Siemens is making the difference in digital interaction, simpler and more connected. Will you kind of walk around and explore more at the booth, or are you tied in business meetings?

R

Rudy5:57:41

Right. I'll be around right on the field, right into the rumble.

C

Christine5:57:44

I just need to change my shoes because looking at my pandemic...

R

Rudy5:57:48

Like cloud9 shoes. They symbolize digitalization and a lot of artificial intelligence. But still I need to walk for myself.

C

Christine5:57:56

Okay.

Big, big time thank you for the time you've been up here on stage. A big applause for my four musketeers in digitalization journey and team Accelerator, making shopping easy. Thank you so much. All the best of luck and success at the fair.

R

Rudy5:58:12

Thank you.

Siemens | Live from Hannover Messe 2026

About Cedrik Neike