by Gary Mintchell | Apr 18, 2025 | Data Management, Manufacturing IT
The Aras ACE2025 Community Event in Boston closed two weeks ago. It has taken me that long to wrap my head around everything I learned. Normally there are many really important-sounding words that sound so enlightening at the time, yet when I sit to write I find no substance. In this case, there was so much substance that I have trouble filtering to the most important themes.
Let’s say that not only were the expected buzz words in evidence but the underlying concepts were demonstrably in use. Aras is a PLM (product lifecycle management) developer. They are solving problems that I had in the late 70s while working at a manufacturer. Mainly, how to make usable sense from all the engineering data.
The principle phrase of the week was digital thread. They are all about the digital thread. Companies were also using Large Language Model (LLM) technology trained on their own data. Agentic AI rears its head and will become even more important with use. (See my interview with John Harrington of HighByte for more on Agentic AI.)
Customer presentations that showcase actual use cases provide reality to the theory.
I sat in a presentation by the sensor manufacturer Sick. They have applied AI to unstructured data turning them into useful structured data. Using Aras PLM, they have realized better speed to market finding product data via natural language query. They have instances of development times cut from 3 years to 6 months.
Another customer presentation came from Denso. Engineers find the digital thread from PLM as a tool for collaboration. The connected flow of data ensures continuity from design to manufacturing to operations. Inconsistent data hurts the business. PLM is the heart of their digital strategy with the BOM as centerpiece. Once again an example of someone actually using GenerativeAI trained on their data to fill in gaps.
The highlight of customer applications came from my half-hour discussion with Tetsuya Kato, Manager of the Technical Management Group from SkyDrive in Japan—the Flying Car company. OK, it’s not the Toyota in your driveway suddenly flying to the store. But it’s close. Check out the goodies on their website.
He was hired to bring order to the product information system. In other words, to develop a better Manufacturing Bill of Materials (MBOM). They were using Team Center PLM with a system brought in by a consulting engineering firm. The system had many problems, was taking too long to implement, and forced SkyDrive to change its systems to fit the software.
Kato brought in Aras Connector to bring engineering data from Team Center to the Aras PLM platform. He started the project in September, showed results in two months, and moved all the data in eight months. The Aras solution had all the features necessary for their manufacturing data with the additional benefit of flexibility to allow them to make the system work for them instead of the other way around.
Chief Technology Officer Rob McAveney asks “What if…”
McAveney noted Aras has 25 years of asking what if…
- 2001 What if PLM could be flexible, webnative platform?
- 2005 What if PLM applications were built to work together? Integrated data now called digital thread.
- 2011 what if impact analysis were an interactive experience? Wizard style digital thread.
- 2014 what if visual collaboration was available to everyone?
- 2021 What if a SaaS delivery model came without compromise?
- 2025 What if we could extend reach of the digital thread? Take advantage of Aras Effect, open, reachability; Aras Portals, apps product data platform, composable PLM apps, low code environment?
The digital thread + AI = Connected Intelligence:
The three areas of Connected Intelligence include:
- Discover—conversation about data
- Enrich—connect more data and people business
- Amplify—maximize impact
- Pursuing all three together
Discover—natural language search, content synthesis, machine learning, text to SQL (natural language prompt to query; what if guided tour how to set effectivity conditions to sync multiple changes (context aware help), then phase in changes with confidence, eliminate rework and supply chain, what if assess global supply of a sourced component before submitting a change request, avoid wasting time on changes; what if you could ask AI assistant to ID common factors while root cause analysis, persistent quality issues become a thing of the past.
Enrich—entity recognition, contextual reasoning, topic modeling, deep learning, what if missing of inconsistent links in digital thread could be easily identified and corrected, patterns, downstream analytics, stop wasting effort on redoing work, what if requirements could be automatically identified and ingested from reliable external data sources, then see next level requirements traceability with dynamic requirements, what if factory floor data could be linked to quality planning parameters, planning for feedback loop.
Amplify—agentic AI, surrogate modeling, generative engineering, reinforcement learning, what if engineer-to-order business could be transformed by leveraging all your past engineering work to create a common variability model, engineer shift for individual customer projects to improving full product line.
by Gary Mintchell | Apr 14, 2025 | Services, Software
Many years ago in a galaxy far away, I actually sold an MRO software solution to one of my clients. Fortunately, I left that position to become a senior editor at Control Engineering magazine never learning how it all worked out.
This news concerns a partnership between an MRO software supplier and a services provider said to deliver “technology technology-drive solutions.”
- Verusen and Advanced Technology Services (ATS) Expand Partnership
- Companies leverage expertise in MRO Supply Chain optimization technology to drive a more efficient, data-driven future
- Partnership empowers tire & rubber company to achieve significant MRO inventory optimization across its North American Plants
Verusen, the industry leader driving AI MRO (maintenance, repair, and operations) supply chain and inventory optimization, announced it has expanded its strategic partnership with Advanced Technology Services, Inc. (ATS), a leading industrial maintenance, technology and parts services provider. The collaboration integrates Verusen’s AI platform with ATS’s deep industrial maintenance and reliability expertise to deliver technology-driven solutions for manufacturers. Today’s news builds on the recent announcement that ATS is now a strategic partner of Verusen’s AI-driven platform in North America. The partnership expands the companies’ reach and ability to assist manufacturers in optimizing demand forecasting and inventory management across their MRO supply chains.
The collaboration’s success is exemplified by its impact on a joint tire and rubber customer, which has realized $10M+ cost reductions through MRO inventory optimization across its North American Plants. This achievement underscores the practical value and significant opportunity the Verusen and ATS offering provides.
The Verusen and ATS Partnership Addresses Key Elements of MRO to drive cost savings and inventory optimization through the following:
- Supplier Tail-spend Management: Negotiating favorable pricing and lead times with reliable strategic suppliers.
- Network Inventory Visibility: Using more robust, AI-driven inventory tracking to monitor real-time stock levels.
- Predictive Maintenance: Using data analytics to predict potential equipment failures and proactively order spare parts.
Verusen’s platform is designed to optimize Maintenance, Repair, and Operations (MRO) inventory management using artificial intelligence, helping businesses streamline their supply chain by providing insights and recommendations based on their MRO data across different systems, ultimately ensuring the right materials are available when needed to minimize downtime and operational disruptions.
by Gary Mintchell | Apr 8, 2025 | Data Management, Generative AI
I’m not talking about the Johnny Rivers theme for a late Sixties Saturday afternoon spy TV show. We’re talking software agents. Some may be secret, but none are men.
I once had an annual meeting with the CTO of a large automation company where I shared (non-privileged) information I’d gathered about the market while trying to learn what technologies I should be watching for.
With artificial intelligence (AI) and Large Language Models (LLMs) grabbing the spotlight at center stage, I’m watching for what technologies will make something useful from all the hype.
I’m looking for a return to the spotlight of these little pieces of software called agents. John Harrington, Co-Founder and Chief Product Officer at HighByte, an industrial software company, believes in 5 or so years from now, LLMs won’t be the game-changer in manufacturing that many expect. Instead, Agentic AI is set to have a far bigger impact.
So, John and I had a brief conversation just before my last trip. It was timely due to the nature of my trip—to a software conference where LLMs and AgenticAI would be important topics—and not just in theory.
From Harrington, “Agentic AI is revolutionizing the tech industry by addressing AI’s biggest limitation—making decisions that are more human like. AI agents are yet another application that analyzes and turns large amounts of data into actionable next steps, but this time they promise it will be different.”
He told me that Agentic AI will become more “human-like” going beyond LLMs. HighByte started up as an Industrial DataOps play at a time when I was just hearing about DataOps from the IT companies I followed. I told the startup team that they were entering a good niche. They have been doing well since then. They extended DataOps with Namespace work and now LLMs and agents.
“AI agents can enhance data operations by providing greater structure, but their success depends on analyzing contextualized data. Without proper context, the data they process lacks the depth needed for accurate insights and decision-making,” added Harrington.
Take an example. An agent can be a way to contextualize data, model an asset. Working with an LLM trained on data specific to the application, it can ask the LLM to scan the namespace to see if there are other assets in the database. HighByte’s can work through OPC, and also works with Ignition from Inductive Automation or the Pi database. It looks for patterns and can propose options as the engineer goes in to configure the application.
Not shy in his forecast, Harrington says the future is agents. They can affect and act on data. They can reach out to a control engineer, operator, quality group. It’s a targeted AI tool focused on one small thing. Perhaps there’s a maintenance agent, or one for OEE, or line quality on a work cell. Don’t think of a monolithic code in the cloud. Rather, think of smaller routines that could even work together helping business like Jarvis in Iron Man. Data is food for these agents, and HighByte’s business is data.
I’ve been impressed with HighByte’s growth and sustainability. Also that they’ve managed to remain independent for so long. Usually software companies want to build fast and sell fast. Watch for more progress as HighByte marries agentic AI with data.
by Gary Mintchell | Mar 28, 2025 | Business, News, Software
The last of four news items this week from Siemens concerns a large software acquisition. A high level Siemens executive told me years ago that the company had learned from earlier mistakes in order to more successfully integrate acquisitions. Events have proved him correct. This acquisition should be very interesting for their customers.
- Siemens extends leadership in simulation and industrial AI as it closes acquisition of Altair Engineering Inc.
- Acquisition strengthens position of Siemens as a leading technology company and expands its industrial software portfolio
- Addition of Altair technology to the Siemens Xcelerator open digital business platform will create the world’s most complete AI-powered portfolio of industrial software and further enhance the most comprehensive Digital Twin
- Acquisition is a cornerstone of Siemens’ ONE Tech Company program Siemens announced today that it has completed the acquisition of Altair Engineering Inc., a leading provider of software in the industrial simulation and analysis market, for an enterprise value of approximately USD 10 billion. With this acquisition, Siemens extends its leadership in simulation and industrial artificial intelligence (AI) by adding new capabilities in mechanical and electromagnetic simulation, high-performance computing (HPC), data science and AI. The addition of the Altair team and technology to Siemens will further enhance the most comprehensive Digital Twin and make simulation more accessible, so companies of any size can bring complex products to market faster.
“We welcome the Altair community of customers, partners and colleagues to Siemens. Adding Altair’s groundbreaking innovations to the Siemens Xcelerator platform will create the world’s most complete AI-powered design, engineering and simulation portfolio. Together, we will help our customers to innovate at the scale and speed that today’s complexity-driven world demands,” said Roland Busch, President Siemens AG and CEO of Siemens AG. “Through the ONE Tech Company program, we will extend our leadership in industrial software. This enables all industries to benefit from the revolution driven by data and AI.”
Integrating Altair’s capabilities in the areas of simulation, HPC, data science, and AI enhances the ability of Siemens to drive more efficient and sustainable products and processes. Now, all Siemens customers, from engineers to generalists, will have access to new simulation expertise, can optimize their high-performance computing processes, create new AI tools and perform data analytics to help accelerate innovation and digital transformation for companies of all sizes.
The acquisition of Altair is part of Siemens’ ONE Tech Company program and will meaningfully increase Siemens’ digital revenue share. This growth program enables Siemens to further expand its strong market position and reach the next level of performance and value creation. Through acquisitions like this, as well as R&D investments into areas including software, AI-enabled products, connected hardware and sustainability, Siemens is clearly prioritizing capital allocation to strategic growth fields.
With the completion of the acquisition of Altair as well as the recent expansions of Siemens’ factories in California and Texas, Siemens has now invested over USD 100 billion into the United States in the past 20 years.
by Gary Mintchell | Mar 28, 2025 | Cloud, Edge, Generative AI
The third of Siemens pre-Hannover news releases concerns Xcelerator Edge with Microsoft Azure IoT Operations.
- Siemens Industrial Edge works seamlessly with Microsoft Azure IoT Operations, making OT and IT data planes fully interoperable for manufacturing
- Edge and cloud data integration enables adaptive production through AI- and digital-twin-powered solutions
- Industrial customers benefit from improved machine performance, product quality and reduced machine maintenance
Siemens announces an extended collaboration with Microsoft in the context of Siemens Xcelerator, Siemens’ open digital business platform, to simplify the integration of information technology (IT) and operational technology (OT) for enterprise customers. By combining Siemens Industrial Edge with Microsoft Azure IoT Operations, customers will benefit from complementary solutions that enable a seamless flow of data from production lines to the edge and to the cloud. This edge-to-cloud data integration enables AI- and digital-twin-powered solutions to improve machine performance, product quality, and reduce machine maintenance.
A core component of the Azure adaptive cloud approach, Azure IoT Operations is designed to seamlessly integrate on-premises industrial edge solutions, like Siemens Industrial Edge, with the cloud, ensuring a continuous flow of data for smarter operations.
In this way, the powerful OT data plane provided by Siemens Industrial Edge works easily with Azure IoT Operations, to create an interoperable OT and IT data plane for manufacturing. The data layer from Siemens Industrial Edge effectively addresses mission-critical production applications such as virtualized control, low-latency closed-loop AI, executable digital twins, or production line-level analytics. It allows manufacturers to deploy responsive, reliable, flexible and secure applications to optimize their operations, reduce costs, and increase uptime and quality. By coupling with Azure IoT Operations, industrial producers can easily leverage this OT data in cloud-based, data-driven use cases to optimize production across sites and gain insights from advanced analytics.
by Gary Mintchell | Mar 28, 2025 | Generative AI, Software
This is the second of four Siemens news items. In the vein of everyone in industrial software is Microsoft’s best friend, Copilot headlines this news. And no news today is complete without mentioning generative AI.
- The Siemens Industrial Copilot, a generative AI-based assistant, is empowering customers across the entire value chain – from design and planning to engineering, operations, and services
- Siemens expands its Industrial Copilot offering with extended capabilities for Senseye Predictive Maintenance
- The generative AI-powered solution will support every stage of the maintenance cycle, from repair and prevention to prediction and optimization
A glimpse of Siemens’ AI strategy:
The Siemens Industrial Copilot is revolutionizing industry by enabling customers to leverage generative AI across the entire value chain – from design and planning to engineering, operations, and services. For example, the generative AI-powered assistant empowers engineering teams to generate code for programmable logic controllers using their native language, speeding-up SCL code generation by an estimated 60% while minimizing errors and reducing the need for specialized knowledge. This in turn reduces development time and boosts quality and productivity over the long term.
Siemens is developing a full suite of copilots to industrial-grade standards for the discrete and process manufacturing industries – and is now strengthening its Industrial Copilot offerings with the launch of an advanced maintenance solution, designed to redefine industrial maintenance strategies.
Bringing it to maintenance
The Senseye Predictive Maintenance solution powered by Microsoft Azure will be extended with two new offerings:
- Entry Package: This predictive maintenance solution combines AI-powered repair guidance with basic predictive capabilities. It helps businesses transition from reactive to condition-based maintenance by offering limited connectivity for sensor data collection and real-time condition monitoring. With AI-assisted troubleshooting and minimal infrastructure requirements, companies can reduce downtime, improve maintenance efficiency, and lay the foundation for full predictive maintenance.
- Scale Package: Designed for enterprises looking to fully transform their maintenance strategy, this package integrates Senseye Predictive Maintenance with the full Maintenance Copilot functionality. It enables customers to predict failures before they happen, maximize uptime, and reduce costs with AI-driven insights. Offering enterprise-wide scalability, automated diagnostics, and sustainable business outcomes, this solution helps companies move beyond traditional maintenance, optimizing operations across multiple sites while supporting long-term efficiency and resilience.
