Just after closing its $10 billion purchase of Altair, Siemens announced that it’s signed an agreement to acquire Dotmatics, a Boston-based developer of life sciences R&D software, for $5.1 billion. (Maybe there was a buy-one-get-one-half-off deal on scientific software companies.)

Siemens characterized the Dotmatics announcement as another milestone in its new ONE Tech Company growth program. I poked some fun at that last week, but maybe Siemens really is trying to form ONE Tech Company to rule them all.

So why Dotmatics? Siemens sees life sciences as complementary to its engineering software portfolio, and wants to cross pollinate its AI and digital twin solutions into a new market.

“By acquiring Dotmatics, we’re strategically strengthening our position in Life Sciences and creating a world-leading AI-powered PLM software portfolio as part of Siemens Xcelerator,” said Roland Busch, president and CEO of Siemens, in the company’s press release.

Or, in CFO speak: “The acquisition of Dotmatics drives strong revenue synergies and is highly profitable and cash generative,” said Ralf P. Thomas, Siemens’ chief financial officer.

Siemens expects the deal to close in the first half of its fiscal year 2026 (Siemens’ fiscal year starts in October), subject to customary regulatory approval.

Will this move pay off? It sure did for Dassault Systèmes. Remember when they bought Medidata, a developer of clinical trial software, for $5.8 billion in 2019? Dassault couldn’t have known that 2020 would bring a global pandemic—but the race to develop a Covid vaccine, and Medidata’s role in that effort, sure made Dassault’s investment in the life sciences company look like a stroke of genius.

Let’s hope the comparison ends here.

Hexagon closes two deals too

In other engineering software acquisition news, Hexagon announced that it’s completed its purchase of 3D Systems’ Geomagic software suite for $123 million. Geomagic applications, including Design X, Control X, Freeform and Wrap, are used for capturing and processing 3D scan data. The software will now be offered by Hexagon’s Manufacturing Intelligence division.

“The combination of Geomagic and our existing solutions will further strengthen our market leadership in 3D metrology and reengineering,” said Hexagon interim CEO Norbert Hanke in the company’s initial announcement in December 2024.

Hexagon also announced that it’s completed the acquisition of Belgium-based Septentrio NV, a manufacturer of GNSS receiver technology. That company will operate within Hexagon’s Autonomous Solutions division.

Quick hits: Updates and integrations

• SDC Verifier launched a new version of its FEA software, SDC Verifier 2025 R1. The release marks a switch to account-based licensing, replacing the former system of activation keys with a personal login. It also adds support for the latest versions of Ansys, Simcenter 3D and Femap, among other updates.
• Dassault Systèmes released Simulia Manatee 2025X R1, the latest version of its simulation software for analyzing electromagnetic noise and vibrations. The release reduces magnetic calculation time by up to 50%, has a better flux density import interface, and adds other new features, according to Dassault.
• Concepts NREC and ADS CFD have partnered to bring the latter’s GPU-accelerated CFD software to AEDS, Concepts NREC’s suite of CAE and CAM software for turbomachinery design. According to Concepts NREC, the integration will enable turbomachinery designers to run CFD simulations 15 – 120x faster than traditional solvers. (Sorry for that avalanche of acronyms, btw.)

One last link

I’m late to this April Fools’ Day joke, but if you’re in the mood for amusement read about the new Onshape desktop client from Caden Armstrong of SmartBench Software. (Don’t skip the comments.)

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

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Let’s start with the $10 billion elephant in the room. Siemens announced that it has completed its acquisition of simulation developer Altair, a deal which has been brewing since last October. In fact, the deal closed ahead of schedule—Siemens initially projected it for the second half of 2025.

A Siemens representative told me that “there should be zero immediate impact to Altair customers.”

I’m sure it won’t be long before something comes from this consummation, but we’ll have to wait and see what the software stork brings.

Meanwhile, it’s interesting that Siemens is now framing this acquisition as part of—nay, a cornerstone of—something called the Siemens ONE Tech Company program.

The program wasn’t mentioned in the original acquisition announcement (dated October 31, 2024), but some intrepid googling leads to a Siemens press release from two weeks later (November 14, 2024) that, amidst a report of the company’s fiscal 2024 performance, nonchalantly announces the initiative.

Here’s the gist: Siemens is pumping more money into acquisitions and R&D. The goal? Take your pick:

• “to achieve the next level of performance and value creation”
• “to ensure that the company leverages the opportunities arising from the historic market shifts that mark a turning point and from [sic] technological disruptions”
• “to achieve stronger customer focus, faster innovation and higher profitable growth”
• “to accelerate the execution of the existing strategy, which is summarized as ‘to combine the real and digital worlds’”

Besides the US$10 billion Altair acquisition, Siemens spent €6.3 billion ($6.81 billion) on R&D in 2024, up from €6.1 billion ($6.59 billion) in 2023.

Seems like Siemens’ ONE Tech Company program is off to a good start. Altair down, a few hundred thousand tech companies left to go.

Motif launches BIM collaboration platform

Motif has officially launched its web-based BIM platform.

The software startup, founded by Autodesk veterans Amar Hanspal and Brian Mathews, emerged from stealth earlier this year with $46 million in funding and a dream: to revolutionize building design.

This debut is just one of many steps towards that dream, Matt Jezyk, VP of product at Motif, told me after the launch. Today Motif’s platform is laser focused on BIM collaboration. It provides a whiteboard-like interface for engineers and architects to brainstorm ideas, review documents and create presentations.

It’s inspired by modern web collaboration tools like Miro, Mural, and Figma, but Motif sets itself apart with support for 3D data—including live, bidirectional plugins for Revit and Rhino. More plugins are in the works, according to Jezyk.

“The first thing that we’re coming to market with is focused on collaborating and reviewing and collecting information from the sources where people are working today,” Jezyk told me.

Lots more details on Motif’s platform and the startup’s vision in Motif launches BIM collaboration app with plugins for Revit and Rhino—check it out, bookmark it, and read it first thing every morning for maximum effect.

Where engineers want to work

Are you an engineer who loves to work—particularly at places? If so, I’ve got just the list for you: the Top Workplaces for Engineers in 2025.

Engineering.com partnered with Energage to compile this list of the best U.S.-based companies to be an engineer, according to employee engagement surveys. The list includes 35 winners in three categories of small, medium and large companies.

Congratulations to the winners. This is an annual program, so if you know of a deserving engineering workplace, why not nominate it for next year’s list.

Quick hits: Update, beta, preview

• IronCAD released the 2025 version of Multiphysics for IronCAD, a simulation extension for the 3D modeling software. Multiphysics for IronCAD 2025 (known to its friends as MPIC 2025) includes new features for design optimization, mesh preparation, visualization and more, according to IronCAD, plus routine updates and bug fixes.
• China-based ZWSOFT released the latest beta of its 2D CAD program, ZWCAD. The developer says that ZWCAD 2026 has new and enhanced features for parametric design, batch editing, dimensioning, plotting and more.
• PTC announced that it will preview its Windchill AI PLM assistant at Hannover Messe 2025, the industrial trade fair taking place this week. The company says the AI assistant will “enable engineers to access information, make decisions, and develop their products more efficiently.” Cool, but I’m still waiting for a preview of Onshape AI Advisor.

One last link

My colleague Ian Wright is in Chicago this week for AMUG, the Additive Manufacturing Users Group, and he shared his first-timer impressions of the unique conference.

(Ian, if you’re reading this, grab some deep dish pizza from Giordano’s and please bring me back a large pie with anchovies and black olives.)

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

The post ONE Tech Company to rule them all appeared first on Engineering.com.

As global markets trend towards sustainable, net-zero economies, aviation finds itself at a crossroads. For decades, airplane geometries have converged. They all contain a large, pressurized tube; massive, petrol-filled wings and a half-dozen-or-so jet — maybe propeller — engines. Interiors have new creature comforts, space saving methodologies and lighter materials, but for generations development has stagnated. Aziz Tahiri, vice president of Global Industries Aerospace & Defense at Hexagon, argues that for the industry to align with sustainability trends, everything must change.

“You have to review everything in an aircraft to be sustainable,” says Tahiri. “Almost everything was designed 40 years ago. You need to reconsider all these systems. This is hard because of the economics and financial systems attached to it. You need to almost reinvent everything, and new product introduction costs a lot of money.”

The obvious first step is to change aircraft power systems. Sustainable aviation fuel (SAF), hybrid and electric systems, green hydrogen fuel cell systems are leading candidates, but which should be selected and how will this selection affect aircraft geometry? Designing, testing and manufacturing the prototypes to answer these questions — while maintaining best practices — will get expensive and time consuming.

“We need to rethink the aircraft without spending ten years to design a new aircraft,” explains Tahiri. “To spend $12 billion to design an aircraft; you need to produce thousands over ten years to break even. We need to reduce the design cycle time to test new materials, fuel and designs to get a new aircraft in six years and maybe $6 billion.”

So, what technologies will make the aircraft industry sustainable: new fuels, batteries, fuel cells? One, or a combination, will inevitably come out on top. But it will be new technologies for high fidelity 3D simulation, traceability and advanced manufacturing that get us there.

How high fidelity 3Dsimulation can make flying green

Simulation technology is by no means new to the aerospace industry. For decades it has been used to validate the structural integrity of components, aerodynamics strategies, test new materials and assess propulsion strategies. What has changed is its accuracy and time to results; this should change how it’s used.

“Yesterday you could not avoid prototyping several times — even up to 3-6 prototypes — and the engineering teams were using simulation to test and validate them more extensively. Today with efficient large model processing, it’s much easier to iterate with an accurate 3D or system model  in the virtual world. So maybe you only need to prototype once to find out if what you make works as designed,” says Tahiri. “That is what we do at Hexagon. We have simulations so close to reality and physical testing we can avoid multiple physical tests and iterations.”

The idea is to reduce design cycle times by replacing the use of physical prototypes with digital alternatives and using them extensively earlier in the design phase. This saves a lot of money and time, as building prototypes as large and complex as an aircraft isn’t easy.

Tahiri explains that this iterative process is becoming even faster thanks to the use of artificial intelligence (AI). The use of AI can significantly reduce the computational time needed to get results. Additionally, AI can be used to suggest iterations to a design, helping engineers zero-in on optimal geometries faster than before.

Using modern simulation and AI, Tahiri suggests engineers start testing:

• Aircraft architectures like delta wings, blended wing bodies and adjustable wingtips.
• Biomimicry to see how bird and insect flight might influence and optimize aerodynamics.
• The performance of materials like composites, and components made via additive manufacturing.
• Propulsion and storage strategies for hydrogen, batteries and fuel cells.

How 3D model traceability tools bring sustainability to aviation

Like simulation, traceability is not new to the aviation industry. Since aviation’s inception, documentation has helped design, certify and justify aircraft designs. What has changed is that traceability is no longer a manual endeavor — almost everything can be digitalized efficiently and accurately.

“You once had an army of inspectors to check everything is signed off and manufactured right,” said Tahiri. “Now we are using automated inspection capabilities with laser scanners that digitally send measurements to certification systems. These scanners can ensure traceability all along the product lifecycle. Instead of having a huge amount of paper for inspection reports, you now have a digital report that correlates to a 3D measurement cloud that can be meshed into a CAD model.”

The detailed 3D measurements add a critical “source of truth” to the digital twin and ensures all stakeholders collaborate on the same data throughout the product lifecycle. For instance, simulation experts can take the measurements from the manufacturing team to ensure a plane, as built, meets sustainability requirements. These geometries can also be used to help process development teams make the manufacturing processes more sustainable — by reducing scrap, for example.

How manufacturing must change to make aerospace sustainable

Since development teams can iterate on a design to reduce scrap, it stands to reason they can iterate on designs to ensure manufacturability — or better still, optimise it virtually before any CAPEX is committed. “Before you certify a new design, you need to make sure it is manufacturable,” Tahiri confirms. “This usually happens after the design of the aircraft. However, we can now simulate the manufacturing processes before a design is signed off and certified.”

This means that — well before any assembling, drilling or fastening — development teams can assess if a design can be manufactured ­and if said manufacturing process meets sustainability goals. “If you engineer something but you can’t manufacture it, or it takes re-engineering every time you do, the ROI is ten years instead of five and the engineering fails,” says Tahiri. “Well-engineered products can be manufactured, and the processes are optimized for quality, cost, sustainability and time to market.”

Hexagon is a trusted partner that works with 90% of the aerospace and defense industry. It enables industry experts to achieve their sustainability goals and overcome their challenges and deliver quality at any stage of the product life cycle. To learn more about how Hexagon enables sustainable aviation, click here and read the white paper.

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There’s more Nvidia-related simulation news to go over today, starting with cloud simulation provider SimScale.

SimScale’s AI foundation model for pump simulation

SimScale announced at GTC that it has developed “the world’s first foundation AI model for centrifugal pump simulation.” It uses AI to quickly predict the results of a full simulation.

SimScale developed the foundation model with Nvidia PhysicsNeMo, Nvidia’s framework for physics-based AI. It’s integrated into SimScale’s platform via Nvidia’s Omniverse Blueprint (see the following item for more on Blueprint.)

SimScale already allows users to develop predictive AI models, but users must train those models themselves. The pump foundation model is different. Jonathan Wilde, vice president of product management at SimScale, told me that the model is already trained on thousands of simulations covering more than 50 pump models with different geometries and operating points.

“We’ve used that data to train a generic pump model,” Wilde said. “If somebody brings a pump to SimScale, they don’t need to pre-train anymore… they can get an instant AI prediction.”

SimScale took the training data from its public projects repository, which includes simulations from SimScale’s Community user tier. Those users get free, limited access to the cloud simulation platform, but their data is openly available (similar to Onshape for CAD). When I asked about the reliability of that public data, Wilde said that SimScale manually validated the simulation setups.

Paying SimScale customers can request access to the pump foundation model, but Wilde says the company hasn’t yet determined how it will license or charge for the technology. SimScale’s non-paying Community users cannot currently access any of SimScale’s AI capabilities, though Wilde said that “will almost certainly change.”

This is just the first of what Wilde expects to be many AI foundation models.

“Pumps are just a starting point. We wanted to start with something that wasn’t too simple, but also not insanely complex,” Wilde told me. “Next we’ll make a valve model, and we’ll just keep iterating from there. It won’t always be CFD, we’ll add some FEA, but we’re going to try and continually build more foundation models.”

Altair integrates Omniverse Blueprint for real time digital twins

Last week Nvidia announced the general availability of its Omniverse Blueprint for real time digital twins. Altair followed up by announcing that the Blueprint is now integrated with the Altair One platform. Altair says that the new integration will give users turnkey access to Nvidia technologies including Omniverse, GPU acceleration and Nvidia NIM microservices.

What is an Omniverse Blueprint, anyways? There’s a fuzziness to how Nvidia and its partners are using the term. A Blueprint, of which there are many, is a reference application for software developers to build on. Tim Costa, senior director of CAE at Nvidia, told me last week that the Omniverse Blueprint for real time digital twins is “an open source demo” to “help our engineering solution provider partners adopt those technologies needed to provide interactive design to their customers.”

So when developers like Altair and SimScale (see above item) talk about integrating Blueprints into their software, it’s not entirely clear what they mean. Altair’s press release paints a broad picture:

“By leveraging Nvidia Omniverse Blueprint for Real-Time Digital Twins in Altair One, users can collaborate and simulate in a shared virtual environment in real time. The technology combines 3D design, AI, and ray tracing to create immersive digital environments that function as a next-level digital workspace… Users benefit from high-end rendering and streaming capabilities on the cloud that simplifies how software components work together in large systems, especially those used for AI, data processing, and graphics computing.”

In other Altair news, the simulation developer announced that aerospace company JetZero is using Altair software to develop a blended wing body airplane, a type of aircraft that offers impressive fuel efficiency if you don’t mind feeling like you’re flying on a roller coaster.

More drama at Autodesk

Last month Autodesk slashed 9% of its workforce. CEO Andrew Anagnost said that the cuts were his decision, but some industry observers speculated that he was responding to pressure from shareholders who were loudly unhappy with Autodesk’s profitability.

Well, they’re still not happy. Starboard Value LP, a hedge fund holding more than $500 million in Autodesk shares, published a letter on March 19 expressing its concerns about “Autodesk’s long history of financial and operational underperformance” and calling for a change to the company’s board of directors. The letter acknowledges the recent staff cuts as “a step in the right direction” but adds that “substantial questions remain about the financial impact of these actions and how much benefit will ultimately be recognized in FY2026 and beyond.”

I can’t say how this corporate turbulence will ultimately impact Autodesk’s software, but if Starboard gets what it wants, Autodesk users probably won’t. What’s good for short-term profitability is rarely good for customers.

One last link

Still trying to understand what Dassault Systèmes is talking about with “3D UNIV+RSES”? I know I am. Engineering.com contributor Lionel Grealou offers some insight in Decoding Dassault’s 3D Universes jargon: combining virtual and real intelligence.

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

The post SimScale pumps up AI simulation appeared first on Engineering.com.

I can’t cover it all here, but you can check out Nvidia CEO Jensen Huang’s opening keynote for two hours of the chipmaker’s strategic vision, a heap of product announcements, some special stage props, and a few self-aggrandizing video interludes.

On the simulation side of things, one of Nvidia’s top announcements was really more of a brag: the company says its Blackwell chips (which were announced at last year’s GTC) are accelerating simulation software by up to 50x.

“We saw up to 50x better performance on a Blackwell chip as compared to a leading data center CPU,” Tim Costa, senior director of CAE and CUDA-X at Nvidia, told me. “This is across a variety of important CAE workloads, from CFD to discrete element methods, finite element analysis, lithography and SPICE simulation.”

Nvidia’s announcement calls out a who’s who of CAE developers that have accelerated their software with Blackwell: Altair, Ansys, BeyondMath, Cadence, Comsol, Engys, Flexcompute, Hexagon, Luminary Cloud, M-Star, Navasto, Neural Concept, nTop, Rescale, Siemens, Simscale, Synopsys and Volcano Platforms, to put it alphabetically.

One concrete example comes from Cadence, which used a Blackwell-based server to run a 10 billion cell aerodynamic simulation of an aircraft during takeoff and landing.

“This is a problem that previously required a TOP500 supercomputer with hundreds of thousands of CPU cores running for days,” Costa said. “But this run was done on a single [Nvidia GB200] NVL72 server in under 24 hours.”

Nvidia concurrently announced the that its Omniverse Blueprint for real time digital twins, first previewed last year, is now generally available. (It’s also called OV RTDT, which my brain can’t help but read as R2D2.)

“The word Blueprint really means open source demo,” Costa said, and this one is meant to help Nvidia’s partners implement real-time digital twins. If you’re at GTC you can see some examples for yourself.

“At the show this week you’ll see real time digital twins of cars, of supersonic jets, of the human heart—that’s a really cool one—and then many other incredible applications from our partners and their customers,” Costa said.

(I’m not at the show this year, so if you see any of those things send me your pictures, thoughts and maybe a fun postcard: malba@wtwhmedia.com.)

So what’s the bottom line of all this boasting?

“Nvidia superchip architectures, combined with advances in AI physics, have created an inflection point in engineering design,” Costa said. “Grand challenges that [were] previously too complex and costly are being incorporated into typical design cycles, and interactive design with real-time digital twins are becoming a reality.”

Speaking of AI physics…

Geometry to simulation to AI

AI-based design optimization is the focus of a new integration between Luminary Cloud, nTop and Nvidia.

Luminary Cloud announced that its APIs can now create a pipeline between its GPU-based simulation platform, nTop’s computational design capabilities and Nvidia’s PhysicsNeMo framework for physics-based AI.

Together the three tools allow users to automatically create geometry, analyze it, and use that data to train predictive AI models.

“NTop generates the geometry and all the parametric changes. You could generate thousands of geometries. Those geometries are fed directly into Luminary [Cloud], which analyzes the physics and produces results,” Juan Alonso, CTO and cofounder of Luminary Cloud, told me.

“Then, leveraging the Nvidia NeMo ecosystem to train models… you could use that model in lieu of the full simulation. Even though we’re very fast, inference from these models is even faster.”

While both Luminary Cloud and nTop offer generic geometry tools, Alonso said the integration will particularly benefit users that routinely rely on fluid or thermal analysis, such as in the automotive and aerospace industries. The developers demonstrated the integration by optimizing the lift and drag characteristics of a flying wing (see below image).

Bradley Rothenberg, CEO of nTop, provided a few more details and images in a LinkedIn post yesterday.

This is the first official collaboration between Luminary Cloud and nTop, but both companies have worked with Nvidia before. Luminary Cloud and Nvidia jointly demonstrated a virtual wind tunnel last November when Nvidia announced Omniverse Blueprints for real-time digital twins (now generally available; see above item). Last September, nTop announced a separate Nvidia integration and an investment from Nvidia’s venture capital arm, NVentures.

Ansys integrates Omniverse

In other Nvidia news, Ansys announced that it will integrate Nvidia Omniverse in some of its simulation software, starting with Ansys Fluent for fluid simulation and Ansys AVxcelerate Sensors for sensor simulation. Other Ansys apps will follow, according to the developer.

The Omniverse integration will allow Ansys users to render photorealistic models directly in the Fluent or AVxcelerate Sensors interfaces, which Ansys says will facilitate simulation data preparation and communication. PyAnsys, Ansys’ collection of Python packages, will further allow users to automatically format simulation data for their own applications built on Nvidia Omniverse.

“The integration of Omniverse technologies within Fluent allows us to visualize complex physics simulations that give us and our customers intuitive insight into how our equipment operates in stunning detail,” said Andrew Hobbs, director of advanced technologies at Astec Industries, in Ansys’ press release.

One last link

Are ants smarter than humans? The evidence is mounting. Read Mark Jones’ Technical thinking: Finally, proof that the Andy Letter was right to prepare for the upcoming war with Paratrechina longicornis.

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

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The VARLab specializes in harnessing advanced simulation and modeling methods to tackle business challenges. Magnetic 3D’s 100-in. glasses-free 3D displays empower researchers to visualize and refine complex layouts, such as manufacturing facilities, in a fully immersive environment. By integrating real-world data, they can test configurations and simulate business processes to optimize efficiency. This smart manufacturing approach enables companies to streamline operations, reduce costs, and refine design, development, and engineering workflows before committing to physical construction. Additionally, linking the digital twin to real-world sensors provides real-time insights for ongoing improvements.

One of the core advantages of digital twins is their ability to provide dynamic 3D simulations of real-world processes. Magnetic 3D’s technology enhances this experience by adding depth perception, allowing stakeholders to step inside the simulation for a more intuitive understanding. This capability is particularly valuable in early-stage concept development, where engineers can use immersive 3D visualization to present their ideas and secure stakeholder buy-in more effectively.

Dr. Carolina Cruz-Neira, a trailblazer in virtual reality and co-inventor of the CAVE (Cave Automatic Virtual Environment), serves as co-director of the VARLab and holds the Agere Chair Professorship at UCF. Her expertise in immersive technologies will help drive innovative applications of holographic 3D displays in digital twin research, further bridging the gap between virtual simulations and real-world implementation.

“We are excited about our partnership with Magnetic 3D because their glasses-free 3D displays have incredible benefits and a lot of utility for many applications in our field,” she said in a press release. “Our research group primarily focuses on modeling and simulation in 3D environments, so we appreciate Magnetic 3D’s platform, which allows us to visualize and collaborate in 3D as a group without having to wear 3D glasses or headsets.”

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First, thanks to all the readers who wrote in about last week’s column, in which I covered Backflip’s new mesh-to-CAD AI tool. Clearly I wasn’t the only one who was intrigued by it.

Reactions generally fell into two camps:

• Wow, how cool is that! or
• AI is one step closer to killing us all.

Which side are you on? Foil my attempts to achieve Inbox Zero by sending your opinions to malba@wtwhmedia.com.

And now the news.

Renesas announces Renesas 365, Powered by Altium

Semiconductor manufacturer Renesas has announced the first fruit of its $5.91 billion acquisition of EDA developer Altium in 2024. Renesas 365, built on the Altium 365 platform, will be released in early 2026 as a new solution for electronics system development.

According to Renesas’ announcement, the new solution “connect[s] Altium’s advanced cloud platform with Renesas’ comprehensive embedded compute, analog & connectivity, and power portfolio… [to] streamline workflows, accelerate time to market, ensure digital traceability and real-time insights, and improve decision-making from concept to deployment.”

Renesas will showcase live demos of Renesas 365 at Embedded World 2025 in Nuremberg, taking place this week from March 11 to 13.

Questions and answers on 3DLive, Dassault’s Apple Vision Pro app

This summer Dassault Systèmes will release 3DLive, an app for Apple’s Vision Pro spatial computing headset that will connect to the 3DExperience Platform.

What? How? Why?

I asked all those questions (though in slightly more syllables) of Tom Acland, CEO of 3DExcite at Dassault Systèmes. He explained 3DLive’s capabilities, the benefits it will bring to users and its place in Dassault’s vision of 3D UNIV+RSES.

“The VR thing’s been done before, but this is a next-generation capability for putting people inside the model,” Acland told me.

Don’t miss the full Q&A with Tom Acland on Engineering.com.

CoreTechnologie improves its CAD simplification software

CoreTechnologie has released a new version of 3D_Evolution Simplifier, its software for CAD model reduction. The update adds rule-based automation features that CoreTechnologie says will make it easier to prepare models for simulation, digital twins, product catalogues, virtual reality and other applications that benefit from simplified 3D models.

Features of the updated 3D_Evolution Simplifier include the shrinkwrap function, which filters out internal components; the bounding shape function, which replaces detailed parts with simplified substitute bodies; the mesh reduction function, which CoreTechnologie says can reduce mesh sizes by up to 98%; and more.

Kisters releases 3DViewStation v2025.0

Kisters has released the 2025 version of its CAD viewing software, 3DViewStation. The biggest update is a simplified user interface. With a reorganized ribbon menu that groups related functions together, 3DViewStation 2025 will require fewer mouse clicks and allow users to be more efficient, according to Kisters.

3DViewStation 2025 also adds the ability to organize views into groups, allowing users with large numbers of views to more easily navigate between them.

Autodesk cuts 9% of workforce

Late last month Andrew Anagnost, CEO of Autodesk, sent a memo announcing a massive 9% cut to the company’s workforce, totaling around 1,350 employees.

Anagnost wrote that the layoffs are a response to shifting corporate strategy, evolving investments in AI and cloud technology, and increasing economic and geopolitical uncertainties. “This decision was made by myself and CEO staff and is not the result of any third-party pressure,” he wrote.

Best of luck to all those affected.

One last link

I leave you with a brief reflection on humanity and its inventions from my colleague Lisa Eitel at Design World: A 1993 mystic on the nature of AI.

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

The post Renesas’ $5.91B Altium acquisition bears fruit appeared first on Engineering.com.

This episode of Designing the Future is brought to you by Bentley Systems.

Engineering is applied science. It’s also an art, the confluence of creativity and blue sky thinking, constrained by physics. For large engineering projects, particularly in the civil engineering space, it’s also about project management. The marriage of great designs, with great planning and high-performance execution delivers projects that arrive on time, on budget and to specification. The bigger the project, the greater the complexity, and problems can scale exponentially with that complexity.

Today, there are new factors. Mass collaboration across a city, a nation or around the world is common for large engineering projects, and it’s a given that very large projects involve more than one software platform. Factors such as regulatory compliance, and data security are also in play, as well as real questions about the emergence of new technology. It’s a big subject, and it’s important.

engineering.com’s Jim Anderton spoke with Julien Moutte, chief technology officer for Bentley Systems, about the current state-of-the-art in big project engineering technology.

* * * 

Learn more about Bentley’s engineering software and digital-twin-powered, AI-driven capabilities for complex and dynamic infrastructure lifecycle.

The post Advanced technology delivers big engineering projects on time and on budget appeared first on Engineering.com.

Engineers in startups and small to medium business (SMBs) wear a lot of hats. This is mostly due to the common product development challenges these new and/or small organizations face:

1. People challenge: the company doesn’t have enough individuals to fill in all the roles.
2. Technology challenge: the company doesn’t have access to every tool to perform optimally.
3. Process challenge: the company relies on undefined workflows with various data silos.

As the ‘technological brains’ behind the operations, engineers are often tapped to find solutions to these issues. This is problematic, as the main objective of engineers and simulation experts is to get products working and onto market faster.

Julien Simon, product manager of NX Performance Predictor, explains how these common challenges can be addressed using simulation-driven design. In this article, he highlights the top three benefits of computer-aided engineering (CAE) — via NX Performance Predictor — for SMBs and startups.

1.     Improved innovation, product quality and performance

The main objective of simulation-driven design is to predict the performance of any given model within the real world. This has multiple benefits including reducing errors in the final design, verifying or testing assumptions and finding flaws early — when they are easier to fix.

Julien Simon uses the example of a design review meeting between marketing and engineering teams. As people see the geometry in the meeting, they may say “it’s a good idea, but they will ask questions. Now you can put your design in a virtual world to assess performance and quality while within the meeting in the real-world. So, you can already give some KPIs in the early phase.”

These real-time assessments around a boardroom not only improve the quality of a design, but they also promote a culture of innovation. If a marketer thinks a product might sell better if it has an extra curve to its profile, then the engineer can test how that curvature affects aerodynamics or structural integrity right before the marketer’s eyes. The engineer doesn’t have to return back to their desk, spend a few days simulating, and then fall behind half-a-dozen other geometry suggestions.

“If you start to discuss the design from the beginning with a lot of people in the company, you can discuss more ideas,” says Julien Simon. “You can discuss it on the 3D design and test it out — live. There are lots of things you can improve when you have a real product in front of you, the usability, the weight, and you can make trade-offs based on what you see. By embracing more proposals of ideas, it allows you to be more innovative and test more solutions.”

2.     Improved product costs and revenue

Simulation-led design offers many methods to save on costs while boosting revenue. Consider the previous examples. As engineers improve the quality of the product — by testing out more innovative ideas from various sources — they are likely to improve a product’s performance in the market. The engineers also improve communications with common stakeholders, simplifying workflows and improving productivity because, as Julien Simon says, “you test the idea as soon as it comes.”

It isn’t just engineers and coworkers that benefit from the ability of simulation-driven design to test customizations; customers benefit, too. “There is lots of customization in products today,” says Julien Simon. “You can purchase a customized bike online and use the simulations from these tools to show the customer if the size of their frame is okay or not. This helps the customization process as it provides guidance.” And with product customizations comes higher sales, market value and customer satisfaction.

From a simulation-driven design perspective, a product’s performance is based on its ability to perform its given task while remaining durable throughout its lifecycle. Thus, engineers can use CAE to improve a design by increasing a products durability or reducing its loads. “It’s a trade-off of weight, cost and durability,” confirms Julien Simon. “That’s why simulation driven design is so important. It’s easier to do this at the start than in the end of the design process as it will cost less to implement.”

Julien Simon also suggests that “70% of costs can be saved using simulation-driven design.” He cites that tools that encourage simulation-driven design, like NX Performance Predictor, streamline development and make better products; this leads to higher sales and lower costs.

He adds that these tools also reduce the cost to train CAE users. What once took weeks of theoretical background and training can now be done in a day. Siemens even offers digital learning tools to help train new users to use CAE.

3.     Improved development workflows and time to market

Speaking of reducing the training to get users to use CAE, this also leads to another big benefit: improving development workflows. There are only so many simulation experts and, in most cases, they are working at capacity. Therefore, if simulation is to help further improve products it must be usable by more individuals.

Julien Simon states there are two ways these improvements can come about. First, simulation-led design tools, like NX Performance Predictor, are designed to work within tools designers are comfortable with. As a result, it can, “demystify the simulation process so more users can use it,” he says. “When you want to broaden simulation to more people, you need to assess the cost of training. For that we see simulation-driven design solutions can be learned in a couple of days.”

The other strategy is to use AI and algorithmic assisting tools like topology optimization. As the AI learns about optimal designs for the industry, it can help guide newer engineers to produce better designs. Meanwhile, topology optimization tools can take input requirements, such as stress, and provide a near-optimal shape based on its given algorithms.

In both cases the output from the tool may not be the final design, but it helps more users get to that near-optimal geometry faster. This way the simulation experts can focus on more pressing models such as final design optimizations, validations and verifications. Additionally, it enables teams to work more concurrently so that a design that might take a week to produce could instead take days.

Why NX Performance Predictor?

Julien Simon notes the importance of high-end simulation to help organizations finalize, verify and validate designs. But for SMBs and startups its important to start with a tool that is scalable, like NX Performance Predictor. This is because it enables engineers to:

• Get prototypes and designs ready as fast as possible.
• Find failures early so that worktime and budgets can be invested optimally.
• Ensure data is collected, used, reused and scaled as the company grows.

He adds that because the tool is integrated into Siemens cloud-based platform solutions it also enables organizations to scale their digital solutions as they need them. “Starting in NX Performance Predictor, you can reuse what you did there, access the licensing system in the cloud to access another tool, and maintain digital continuity. For instance, you can dig deeper into the design in the Simcenter Portfolio as the start-up grows into a larger company.”

To learn more about NX Performance Predictor and how it can scale with a growing organization, visit Siemens.

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The ideal digital thread connects, in a complete, transparent, and seamless flow, all data and information from any relevant domain (e.g., engineering, manufacturing, quality, service) or solution (PLM, CAD, ALM, SLM, and so on) that defines a product. The digital thread enables efficient collaboration and decision-making throughout the product lifecycle.

As defined by CIMdata, the digital thread is “a communication framework that connects data flows, which can be used to produce an integrated and holistic view of an asset’s data from physical and virtual systems (i.e., its digital twin) throughout its lifecycle across traditionally siloed functional perspectives.” Also connected to the product’s or system’s digital thread are the bills of materials (BOMs) for engineering, manufacturing, and service.

That’s the ideal—everything in the lifecycle connected end-to-end—but everyday reality falls short. Digital threads offer huge benefits but often have breaks; accumulating those connections and related benefits is a never-ending journey. The practical approach is to implement subsets of digital threads based on business benefits; eventually, unbroken connectivity is achieved.

The digital thread can connect many types of simulation, the best known being finite element analysis (FEA) and computational fluid dynamics (CFD). The simulation market is diverse, and many specialized solutions are used for specific products and applications. Companies also create proprietary solutions when they believe it will give them a competitive advantage.

Beyond physics-based solutions, model-based systems engineering (MBSE) is a sophisticated approach to simulating overall product performance by managing requirements, functional design elements, logical design elements, and the physical product definition (i.e., usually an engineering bill of materials or BOM or structure). This approach is also called Requirements Functional Logical Physical (RFLP).

Variation is typically specified by engineering using tolerances on dimensions, GD&T symbology, and with textural notes for  manufacturing planning and quality. Every manufacturing process has variation, some more than others. Because precision adds costs in manufacturing, engineers want to allow as much variation as possible in parts and assemblies while still meeting part interchangeability and performance requirements. In general, more allowable variation lowers manufacturing costs. Engineers and managers work endlessly to account for variability and reduce its negative impact on cost and product performance. In the best cases, they leverage variation to optimize product cost.

Historically, variation specifications were captured on 2D drawings generated “downstream” from 3D models as drafting objects. These specifications drive downstream processes such as product performance analysis, manufacturing planning, CNC programming, and inspection. Engineers should assign variation—tolerances, including dimensional, GD&T, and manufacturing notes during design when they are thinking about how the product functions. But ordinarily, variation is assigned after the 3D modeling is done and in graphical form (rather than as numeric data) which is hard for other software to consume. As a serial process, the design release timeline is extended, and downstream applications such as manufacturing planning cannot start until drawings are released.

GD&T—geometric dimensioning and tolerancing—the best-in-class way to specify variation, is a complex language. GD&T requires syntax and application validation to ensure it is correctly applied. When this is done as a manual checking function, it happens late in the development cycle, when changes are usually the costliest. (Tools exist within CAD solutions, either natively or from third parties, to validate GD&T by ensuring the syntax is correct, reducing the need for manual validation.)

In recent decades, CAD solution providers have moved beyond drafting-oriented GD&T by using Product Manufacturing Information (PMI), which enables variation specifications to be associated directly with the 3D model. A 3D model with PMI is the sum total of data and information manufacturing needs to realize a product: geometry, dimensions and tolerances, Q/A and Q/C datum points, material specifications, surface finishes, annotations for manufacturing, production planning in CAM, and so on.

PMI data can be consumed by downstream applications associatively within the digital thread, reducing transcription errors and enabling shorter, more accurate change cycles downstream.

Historically, variation analysis, including stack-ups, has been done manually or in disconnected spreadsheets. More recently, stack-up and other analysis tools read PMI data to analyze variations and their impact on tolerances or to specify processes directly linked to 3D CAD models. As designs change, analyses becomes easy since it is incorporated directly within the digital thread, enabling variation simulation to keep up with changes, improving the assessment of the impacts of downstream changes in process planning for manufacturing, the accuracy of cost planning, and the predictability of product performance.

Poor change impact analysis can lead to rework, shipping delays, and product recalls. Modern analyses that use PMI reduce these risks.

Tolerance stack simulation—connecting the threads

One of PMI’s benefits is that it enables the building of 2D and 3D tolerance models. These models predict the variation of parts based on tolerance values and GD&T callouts and can predict assembly variation, supporting manufacturing and product performance. For example, tolerances on hole patterns in mating parts, such as a purchased motor and a fabricated mounting bracket, can be used to determine whether parts will fit all the potential tolerance values.

The latest software tools will suggest component tolerances to manage assembly variation to lower costs and improve product performance. Tolerances that have a significant impact are reduced, and tolerances that do not are relaxed. This optimizes product cost since less precise processes can be used on non-critical dimensions and features.

Reliable data linking requires a PLM solution that manages data configuration and related processes. Once PMI is encoded in CAD data, it can be consumed by native downstream applications such as CAM or third-party applications that use the CAD API or via the STEP protocol. When changes happen, downstream files are flagged as impacting the PLM solution and can be reviewed and updated as needed.

Incorporating variation simulation within the digital thread enriches product information and makes it easier to access and use for impact analysis and traceability inquiries. Better variation management improves cost, quality, and time-to-market.

Integrating variation analysis and the digital thread drives many business benefits:

• Finding issues and problems earlier to improve quality.
• Facilitating Shift Left initiatives for completing engineering tasks, analyzing choices, and reaching decisions as soon as possible, shortening time-to-market.
• Making data more consistent and processes more repeatable.
• Upskilling the engineering workforce with better knowledge capture to offset the retirements of experts and the difficulty of replacing them.
• Raising confidence in a product’s design before capital is committed to it.

With all this in mind, it’s optimal to implement the digital thread in subsets keyed to expectable business benefits. Variation analysis is a powerful capability that increases in value when incorporated into the digital thread.

Tom Gill, Principal Consultant & Practice Manager for PLM Enterprise Value and Integration CIMdata Inc.

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