by Gary Mintchell | Jan 12, 2026 | Automation, Data Management, Generative AI, Manufacturing IT, Software, Technology
Siemens seems to have found a home at CES over the past few years. I don’t know what it costs to give a keynote, but it’s probably well worth it, since no other major automation supplier seems to attend. I did write about a robotic exhibitor in my last post. Oh, and I’m still not likely to travel to Las Vegas for the next CES. I’ll save a ton of money and grief by receiving the news at home.
Siemens has maintained strong collaboration with Microsoft for decades—see all the Copilot news below. Recently, NVIDIA has joined the collaboration dance. Also, see news below. I think Siemens thought they’d gain penetration into the North American market through Chrysler’s acquisition by a German company plus the plants constructed by VW and BMW. That market is not so hot—see the proportion of sales into automotive by competitor Rockwell Automation, for example. Check out the customers featured by Siemens at CES this year: PepsiCo, Commonwealth Fusion Systems, Meta Ray-Ban, and Haddy.
Perhaps the best acquisition, and most successful, that Siemens ever made was with UGS years ago. While rivals have struggled with software (and competitors have nibbled at some of the Siemens applications), Siemens continues to strengthen Xcelerator and Copilot technologies. And check out the launch of Digital Twin Composer. Digital Twin technology and application seems to be finally gaining traction.
In short, Siemens announcements:
- Siemens and NVIDIA expand their partnership to build the Industrial AI Operating System, reinventing the entire end-to-end industrial value chain through AI – from design and engineering to manufacturing, production, operations, and into supply chains.
- Siemens launches Digital Twin Composer software, available on Siemens Xcelerator Marketplace mid-2026, to power the industrial metaverse at scale
- PepsiCo using Siemens Digital Twin Composer to simulate upgrades to its facilities in the U.S. with plans to scale globally
- Siemens unveils nine industrial copilots to bring intelligence across the industrial value chain
- Siemens highlights new technologies for accelerating drug discovery, autonomous driving and shop floor efficiency
“Industrial AI is no longer a feature; it’s a force that will reshape the next century. Siemens is delivering AI-native capabilities, intelligence embedded end-to-end across design, engineering and operations, to help our customers anticipate issues, accelerate innovation and reduce cost,” said Roland Busch, President and CEO of Siemens AG.
“Just as electricity once revolutionized the world, industry is shifting toward elements where AI powers products, factories, buildings, grids and transportation. Industrial AI is no longer a feature; it’s a force that will reshape the next century. Siemens is delivering AI-native capabilities, intelligence embedded end-to-end across design, engineering and operations, to help our customers anticipate issues, accelerate innovation and reduce cost,” continued Busch. “From the most comprehensive digital twin and AI-powered hardware to copilots on the shop floor, we’re scaling intelligence across the physical world, so businesses realize speed, quality and efficiency all at once. This is how we scale a once-in-a-generation technology shift into measurable outcomes.”
Siemens and NVIDIA are expanding their partnership to build the Industrial AI Operating System – helping customers revolutionize how they design, engineer, and operate physical systems. They will work together to build AI-accelerated industrial solutions across the full lifecycle of products and production, enabling faster innovation, continuous optimization, and more resilient, sustainable manufacturing. The companies also aim to build the world’s first fully AI-driven, adaptive manufacturing sites globally, starting in 2026 with the Siemens Electronics Factory in Erlangen, Germany, as the first blueprint.
To support development, NVIDIA will provide AI infrastructure, simulation libraries, models, frameworks and blueprints, while Siemens will commit hundreds of industrial AI experts and leading hardware and software. The companies have identified impact areas to make this vision a reality: AI-native EDA, AI-native Simulation, AI-driven adaptive manufacturing and supply chain, and AI-factories.
Integration with Siemens software.
Siemens also announced that it will be integrating NVIDIA NIM and NVIDIA Nemotron open AI models into its electronic design automation (EDA) software offerings to advance generative and agentic workflows for semiconductor and PCB design. This will both maximize accuracy through domain specialization and significantly lower operational costs by enabling the most efficient model to handle and adapt to every specific need.
Product Launch
Siemens’ primary product launch at CES 2026 is the Digital Twin Composer, available on the Siemens Xcelerator Marketplace mid-2026. This new technology brings together Siemens’ comprehensive digital twin, simulations built using NVIDIA Omniverse libraries, and real-time, real-world engineering data.
With the Digital Twin Composer, companies can create a virtual 3D model of any product, process, or plant; put it in a 3D scene of their choosing; then move back and forth through time, precisely visualizing the effects of everything from weather changes to engineering changes. With Siemens’ software as the data backbone, the Digital Twin Composer builds Industrial Metaverse environments at scale, empowering organizations to apply industrial AI, simulation and real-time physical data to make decisions virtually, at speed and scale. Digital Twin Composer is part of Siemens Xcelerator, an industry proven portfolio of software used by companies worldwide to develop digital twins.
Customer application of digital twins
PepsiCo and Siemens are digitally transforming select U.S. manufacturing and warehouse facilities by converting them into high-fidelity 3D digital twins that simulate plant operations and the end-to-end supply chain to establish a performance baseline. Within weeks, teams optimized and validated new configurations to boost capacity and throughput, giving PepsiCo a unified, real-time view of operations with flexibility to integrate AI-driven capabilities over time.
Leveraging Siemens’ Digital Twin Composer, NVIDIA Omniverse libraries and computer vision, PepsiCo can now recreate every machine, conveyor, pallet route and operator path with physics-level accuracy, enabling AI agents to simulate, test, and refine system changes – identifying up to 90 percent of potential issues before any physical modifications occur. This approach has already delivered a 20 percent increase in throughput on initial deployment and is driving faster design cycles, nearly 100 percent design validation and 10 to 15 percent reductions in capital expenditure (Capex) by uncovering hidden capacity and validating investments in a virtual environment.
New Industrial Copilots Streamline Manufacturing Operations
Siemens also spotlighted its partnership with Microsoft highlighting co-building the industrial copilot.
Siemens also announced that it is expanding its set of AI-powered copilots across the industrial value chain. This will embed intelligence that extends from design and simulation to product lifecycle management, manufacturing, and operations.
Siemens will deploy nine new AI-powered copilots for its software offerings, this will include Teamcenter, Polarion, and Opcenter. These copilots, respectively, streamline product data navigation, reducing errors and accelerating time to market; automate compliance, helping to ensure faster regulatory approvals and lower risk; and transform manufacturing processes, driving cost savings and operational efficiency.
These copilots, along with the rest of Siemens’ expanding portfolio of industrial AI solutions, are available to companies of every size on the Siemens Xcelerator Marketplace.
AI-Driven Innovations in Life Sciences, Energy and Manufacturing
- Siemens acquired Dotmatics whose Luma platform enables scientists to unify billions of data points generated across instruments and labs, creating a coherent foundation for AI-driven exploration. Combined with Siemens Simcenter simulation and digital twins, teams can rapidly test molecules, identify promising candidates, and virtually scale production to help life-changing therapies reach patients up to 50% faster and at a lower cost.
- Bob Mumgaard, CEO and co-founder of Commonwealth Fusion Systems, described how the company uses Siemens’ technologies as it leads the path to commercial fusion. Commonwealth Fusion Systems uses design software and a strong data backbone to help it accelerate the development of fusion machines that promise clean, limitless energy for generations to come.
- In manufacturing, Siemens announced a collaboration to bring Industrial AI to Meta Ray-Ban AI Glasses. With hands-free, real-time audio guidance, safety insights, and feedback, shop floor workers will feel empowered to solve problems efficiently and confidently.
- Haddy is reshaping manufacturing through AI-powered 3D printing and localized micro factories that deliver sustainable, high-quality products faster and closer to customers. Facing challenges around supply chain disruption, sustainability, and production agility, Haddy partnered with Siemens to streamline design, optimize operations, and scale efficiently.
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by Gary Mintchell | Jan 8, 2026 | Automation, Software
I’m catching up on some pre-holiday news. Companies have been developing custom packages to (hopefully) make things easier for customers to know what to purchase and apply. This is a unique little package. Siemens is offering a starter pack for small and medium sized businesses in order to “enhance operational efficiency.”
The Siemens prelude and justification, “With the U.S. industrial sector projected to face 1.9 million unfilled jobs by 2032, according to Deloitte, and equipment failures causing up to 20% production losses, SMBs are under pressure from workforce shortages, costly downtime, rising operating costs, supply chain disruptions and the complexities of adopting Industry 4.0 technologies.”
“Small- and medium-sized manufacturers are the backbone of our economy and they are dealing with a different set of challenges compared to enterprise-scale manufacturers,” said Chris Stevens, president, Siemens Digital Industries, U.S. “Among these are transparency to performance, workforce readiness, technology integration, cybersecurity, and productivity.”
The offer
For SMB manufacturers navigating today’s complex production landscape, the Siemens Xcelerator portfolio offers a transformative solution. Its open digital business platform provides solution-as-a-service — and includes the innovative new SMB Production Optimization Starter Pack manufacturing software, which includes the Siemens Industrial Edge Management Cloud and Industrial Edge Virtual Device. These cybersecure tools empower end users to pay for what they need and scale at their own pace.
Siemens has made this digital transformation journey accessible through a three-month free trial, followed by an affordable annual subscription. This comprehensive package includes technical support, self-paced training, and the invaluable expertise of Siemens’ robust network of trusted partners across the U.S.
Siemens’ partners, including PROLIM, are instrumental in delivering the SMB Production Optimization Starter Pack to market, providing localized support, hands-on implementation assistance, and tailored guidance to ensure a truly seamless and supported digital transformation.
Typical of software press releases, here is the use case using cool generic terms. But I still think it’s a good idea.
The SMB Production Optimization Starter Pack provides real-time insights and flexible dashboards and reporting, empowering manufacturers to evolve from reactive problem-solving to proactive operational excellence. This integrated, modular solution is agile, flexible and scalable, and is designed for easy implementation without specialized IT skills or complex infrastructure changes.
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by Gary Mintchell | Dec 16, 2025 | Design, Software
I delve into the world of Product Lifecycle Management, CAD, CAM, Product Data Management, and the like a few times a year. A few supplier companies have invited me to their user group conferences over the past few years. A recent interview was with the new CEO of a cloud-based PLM product who also talked extensively about the coming expanded use of Artificial Intelligence or AI.
So many press releases come my way touting AI that I wonder if it’s only a marketing term. How much is real…and how much is hype?
One thought leads to another, and I wound up on a Microsoft Teams meeting with two people from PTC. Not unlike other companies, PTC discovered it would be much better to acquire a cloud-native company than to try to reinvent the wheel. Enter Onshape.
Last week Darren Henry, SVP Onshape General Operations and Cody Armstrong, Sr. Director Onshape AI Innovation discussed the benefits of cloud-based software (something I’ve written about for years) and how AI is far more than marketing hype. I offered Cody that challenge, and he stood up to that challenge. This is a longer than average post for me, but it was a longer than average conversation 🙂
I’ve had conversations with people from PTC, but there has never been one with Onshape. So, Darren provided an overview. Like I mentioned, I don’t need to be sold on the benefits of cloud-based software for manufacturing. It allows enhanced version management, change tracking, and scaling.
He offered the example of a company sending drawings to selected suppliers in order to obtain quotes. When you send the file, well, they have the file. Can you trust what they will do with your proprietary intellectual property? If you allow sessions on the cloud platform with restricted permissions, then you have more control over the process. Of course, the winning bidder will use the latest approved drawings for building the parts or fabricating. And everything is traced.
Switching over to Cody, whose task was to convince me that AI is real, a useful tool for designers.
“But the first thing that would point out is AI-powered design assistance. We call it AI Advisor. We believe it’s an industry leader. It’s available to millions of users today and the reception has really been fantastic.”
It’s a Large Language Model trained not on the world at large but on the company’s own database and standards. So, like LLMs you may be using now, he adds, “You can ask questions inside of Onshape about how to use Onshape and it will give you a tailored answer to that response. And that answer is much more accurate than what you would get with ChatGPT or any other traditional LLM.
“We’ve built our own layer on top of it that augments that data with our own learning materials, essentially defines it as a source of truth. And so we believe this is the new way that people will learn to use Onshape. And over time, you know this will become more and more.”
Another benefit of AI Advisor is training. “One of the things that that we’ve often found with parametric CAD in general is that it’s very difficult to learn, very difficult to use for a new user. Even if you have experience with a CAD system, learning a new CAD system is difficult. And so what we really set out to solve with the AI Advisor is the ability to quickly answer a user’s question, especially as they’re learning.”
From here, we got into previews of coming attractions.
Another cool use of LLMs comes from language ability. “Another big benefit of A I is we get localization and translation as a tool of the LLM. And many of these localized LLMS support many different languages. We can support those languages as a byproduct of that. So we’re really excited about being able to answer questions in any language, including languages that our product doesn’t even support.”
The next cool tool is FeatureScript. Cody continued, “The next topic that I wanted to bring up is FeatureScript autocomplete. FeatureScript is a language that that we’ve developed for building CAD geometry. It’s very like JavaScript like. You build custom features. They allow you to take all these tedious tasks and turn it into a single feature. It just allows you a quick, easy way to create a feature that’s tailored to you.”
A side benefit—it enables an average design engineer to do software development, which accelerates development.
Search has been around for decades, but it doesn’t seem to be getting better overall. Cody discussed Onshape’s coming use of AI-powered search. “We will initially launch this hopefully in the Public Space. They have a library of of millions of models that are publicly available that users have created using Onshape. We want to allow users to quickly find information in that giant list of documents. We think A I is really well suited for that.”
The AI-powered rendering engine is cool. As Cody explained, “This is a topic I think a lot of people will really appreciate. Rendering can somewhat be a tedious, time consuming task. It can often take 30 minutes to an hour to generate a good rendering of an object in CAD.”
The process begins with the CAD model. You incorporate the background and realistic materials. We can generate professional grade renderings with nothing but a simple prompt, right? And using the latest generation A I image generation models, we can really get amazing results in seconds as opposed to 30 minutes or an hour in more complicated. We call it AI quick render because you can go from a model to a rendered image in a background that looks good in seconds, right?
The last thing I’ll mention, and the furthest down the road for development, concerns AI Agents. They consider agents as simply part of the team. I recently attended a conference where the speaker mentioned a future release containing Model Context Protocol (MCP). The “influencer” sitting beside me almost gave me a bruise on my thigh hitting me with abundant excitement.
Well, Onshape is working on their MCP application.
“So it becomes a tool for productivity that the company can benefit from. But importantly, our architecture will allow for this,” Cody explained.
“It will allow us to say this is a company specific agent with specific permissions that only certain users can access. We we scope that in a very narrow way. It’s a toolkit for other companies to build Agentic workflows into your software. So if you’re a company using Onshape, and maybe you want to build your own agents, we want to allow and enable that. This will allow companies to build their own agents and set their own definitions and communicate with Onshape through MCP interaction.”
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by Gary Mintchell | Nov 17, 2025 | Leadership, Manufacturing IT, Marketing, Software
Aras, a PLM developer, appointed a new CEO a couple months ago (see Aras Appoints Leon Lauritsen as Chief Executive Officer). Our schedules finally coalesced for a conversation.
I’ve been invited to two Aras community events over the past two years. Prior to that, my PLM market knowledge was dominated by three companies. To be honest, I’d never even heard about the company. With one visit and a few interviews, I knew there was something different and better here. (See this report from this year’s event Agentic AI, SaaS, Community—The Aras Community Gathering.)
Aras holds a smaller market position (based on conversations, not market research—something I shun), but it offers something that larger companies don’t. Enterprise and manufacturing software developers usually require users to change their operations systems to fit within the constraints of the software system. Aras provides a more flexible system—something that both Aras product people and customers have told me.
Lauritsen worked for a partner called Minerva for many years prior to its acquisition by Aras. He has held a couple positions within Aras mostly in sales leadership. His background also includes programming and product management—providing him with a background to lead the company in its next iteration.
Aras was a founder-led company until growth required someone to provide professional organization and systems. That leader was Roque Martin. After four years, the board felt it was time for the next step. Lauritsen told me this next step is to incorporate AI into the offerings. In fact, he looks to have the company “supercharge with AI.” He obviously didn’t get into the AI weeds, but I gathered the impression that his product people are working with a variety of approaches for the best fit for each application.
He starts with the customer as he defines his vision of the company. PLM defines the best ways of working for the customer. He has the company working in its labs to find innovative ways to implement AI for both within the organization’s development team and for best practices for customers.
Interesting given my recent work with organizations seeking data interoperability, Aras is seeking ways to coexist with current enterprise solutions.
Many times conversations with company spokespeople center on the product. I asked Lauritsen to define business values provided to customers. He told me about two customers at about the same stage of market development. One used the Aras PLM solution to improve systems to increase quality. The other had a different problem—product development time to launch. Aras provided solutions to fit the business need of the client.
While researching for the interview, I saw that Lauritsen had been on the Danish national Judo team and remains on the national Judo board. Judo requires as much mind training as physical training. So, I had to ask how Judo helps his thought process as a leader and marketer. He laughed, saying the other Aras folks on the call had probably heard enough about Judo. He gave an example from strategic marketing. The principle of Judo is to use the opponent’s force against them. When you face a larger opponent, you know you cannot directly engage, but you must look for the weak point where you can leverage their size agains them.
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by Gary Mintchell | Oct 28, 2025 | Asset Performance Management, Data Management, Manufacturing IT, Software
AVEVA updated its software offering by converging all data into its Connect platform.
AVEVA is converging all data onto CONNECT industrial intelligence platform. Through enhancements to AVEVA Asset Information Management, AVEVA System Platform and AVEVA PI Data Infrastructure, AVEVA can enable the visualisation of engineering and operations data in one interface. This offers organisations the ability to scale digital twin solutions more flexibly and reduce IT overhead.
At this year’s Schneider Innovation summit, AVEVA is showcasing its solutions and vision for its industrial digital twin.
For AVEVA Asset Information Management, the new enhancements will bring together trusted asset contexts, accessible through the CONNECT visualisation offering a single flexible and unified UI to visualise trusted engineering, asset and maintenance data. From P&IDs, drawings, and documents to real-time sensor readings, process events, and historical performance metrics, teams can view and analyse all relevant data in one place.
Meanwhile, AVEVA PI Data Infrastructure is an ever-advancing modern and flexible foundation for rapidly connecting, contextualising and acting on industrial insights from operations data. Its sophisticated data management capabilities continue to drive value across enterprises and new enhancements ensure enhanced hybrid connectivity, visualisation and analytics for AVEVA’s industrial digital twin.
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by Gary Mintchell | Oct 14, 2025 | Generative AI, Manufacturing IT, Operations Management, Software
I am passing this on from the Peter Diamandis newsletter. I don’t think I can link, but click the link on his name to go to his website and sign up. Diamandis sometimes climbs over-the-top optimistic. But that’s a great counter to the usual cynicism and negativity and dysfunctional thinking prevalent in today’s society.
Understanding artificial intelligence (called by Om Malik “augmented intelligence” and by others as neither artificial or intelligent) today requires a healthy dose of realistic thinking and perspective. I offer these thoughts as a counter to your usual AI hype.
Traditional companies are failing to implement AI effectively. Here are five principles to make the technology actually work for you…
1/ AI problems are rarely AI problems – they’re strategy problems disguised as technology problems. Most organizations fail at AI implementation not because they chose the wrong models or hired the wrong engineers, but because they never clearly defined what business problem they’re solving. They see competitors “using AI” and panic-buy solutions for problems they can’t articulate.
2/ Budget size is inversely correlated with AI success. The companies throwing millions at AI initiatives are systematically outperformed by teams running on shoestring budgets with clear mandates.
3/ The 10x rule is the only rule that matters for AI adoption. Anything less than a 10x improvement in speed, cost, or quality is organizational noise. Most AI projects deliver 20-30% improvements that get lost in measurement error and change management overhead.
4/ Competitive intelligence is your fastest path to AI advantage. While you’re debating whether to build or buy, your smartest competitors are already shipping AI-powered solutions.
5/ Pirates beat committees every time. The worst way to implement AI is through enterprise-wide initiatives with steering committees and governance frameworks. Instead, empower your teams from the ground up. Recent studies indicate some alarming news:
- 42% of executives say the process of adopting generative AI is tearing their company apart
- 41% of Millennial and Gen Z employees admit they’re sabotaging their company’s AI strategy
- What’s needed is to enable small teams, “pirate ships,” to move at startup speed (within enterprise contexts). Small teams are optimized to experiment and learn rather than aim for consensus. Give them a problem, a budget, and air cover, then get out of their way.
Here’s the key implementation insight: AI amplifies existing organizational capabilities (and dysfunctions).
