Siemens Digital Industries Software

This week, 90,000+ manufacturing professionals gathered in Chicago for #IMTS2026, North America’s largest manufacturing technology show. But the conversation wasn’t just about what’s next — it was about what’s possible now. Across the show floor, manufacturers were asking how Industrial AI, connected engineering and digital manufacturing can solve real challenges and deliver value today. We brought that question to life at our booth, demonstrating how an AI-powered digital thread can connect the journey from design to manufacturing to help manufacturers turn ideas into quality parts faster. 💡A few key takeaways from the show: • One AI-powered digital thread connects the manufacturing journey: Visitors saw how our CAD, CAM, additive manufacturing, robotics and CNC systems can work together to connect design, manufacturing and production • #IndustrialAI becomes part of the design workflow: Designcenter AI Copilot showed how AI can help engineers automate workflows and guide them through complex design tasks • AI-assisted CAM accelerates CNC programming: The AI-powered capabilities available in Siemens CAM software helps automate repetitive tasks and empowers programmers to create complete machining processes faster while keeping human employees in the loop for final decisions • Manufacturers are eager to adopt AI CAD/CAM workflows: The conversation is moving beyond what AI could do and toward practical applications that understand industrial context and can deliver value within existing engineering and manufacturing workflows • Getting productive faster starts before the machine arrives: With initiatives like Meet at the Machine, announced at IMTS 2026, we're bringing engineering software, automation and machine expertise together to help manufacturers reduce ramp-up time and reach productivity faster The future of Industrial AI in manufacturing isn’t just something on the horizon. At IMTS 2026, we saw it taking shape on the show floor. #CAD #CAM #DigitalThreads IMTS - International Manufacturing Technology Show

The same technology empowering digital transformation is fueling winning race teams from behind the scenes. In a recent interview with The Engineer UK, our Global Head of Automotive Uday Senapati discussed the automotive industry's evolution from the days of physical trial and error to virtual prototyping and how Siemens, as the official Digital Twin partner of the #FIA and tech partner for winning teams including Red Bull Racing & Red Bull Technology, Luna Rossa Prada Pirelli Team and Orient Express Racing, helps accelerate this success with Siemens Xcelerator. A few key takeaways: 🤝 We support our racing partners at three key levels 1️⃣ Discrete simulation: Modelling individual components or systems in isolation to test one set of variables at a time. 2️⃣ Comprehensive Digital Twins: Unifying simulations into a single interconnected model of an entire machine to explore how individual variables work together. 3️⃣ Data and product lifecycle management: Managing and unifying the large amounts of data that elite sport generates. 🌐 Engineering culture is changing. Virtual prototypes are more controllable, repeatable and faster to iterate, a must for competitors working against the clock. 🏎️➡️🚗 Motorsports developments inspire consumer car innovation. Engineering structures and data about weight reduction, crash performance, aerodynamic efficiency and safety provide models and data for road car development, informing newer products like EVs.

Before we let go of summer, let's talk gelato and science! The perfect taste comes from chemistry. 🍦 The perfect look comes from physics. 🍦 To present consumers with premium swirled artisanal packaged gelato, manufacturers require machines capable of balancing the variegation of flavors for that ribbon-like aesthetic. When the machines couldn't keep up, they turned to R&DCFD. This leading Italian engineering company uses their expertise in CFD to help customers across industries with complex problems. In this case, machinery with a static design that struggled to mix ice cream and sauce, exposed the product to air and was difficult to clean. R&D CFD utilized Simcenter STAR CCM+ software and Simcenter HEEDS software to explore hundreds of design variations, testing flow and thermal dynamics, examining complex geometries and optimizing configurations before settling on a final design. In the end, customers got to enjoy gelato that looks as good as it tastes and R&D CFD: 🍨 Modeled 2,000 design scenarios 🍨 Reviewed 80 feeding chamber designs 🍨 Improved designs to be used across all manufacturing plants 🍨 Saved time and money by reducing the number of physical prototypes For more details and designs: 🔗⬇️

Is trust the biggest barrier to AI adoption? 🛡️ According to recent IDC research, trust, security, and data access have become "non-negotiable," outranking even cost and technical skill as the main determinants for AI adoption. #IndustrialAI addresses these concerns head-on: ✅ Embedded security & governance ✅ Ready-to-use tools (no need to build from scratch) ✅ Measurable outcomes across design, realization, and optimization Read more about the shift toward practical, integrated Industrial AI in our latest LinkedIn article: https://sie.ag/7UKnWQ

📢Just announced: We've been named a Leader in the Gartner ® Magic Quadrant™ for Global Industrial AIoT Platforms. We believe this recognition reflects the innovative capabilities of our Insights Hub industrial IoT as a service solution and its leveraging of our Intelligence Center X agentic enterprise system, which empower manufacturers to run smart operations, improve performance and resilience and accelerate continuous improvements with AI and analytics capabilities. Read the press release for more about our AIoT software and insights from Dr. Ralf M. Wagner, our senior vice president, Insights Hub: https://sie.ag/2XPrqB

"AI is only as good as the data underneath it." 💡 At Realize LIVE, our CEO Tony Hemmelgarn laid out a powerful vision for the future of engineering: industrial intelligence. In a world that changes faster than any plan- much like a wildfire- clarity is survival. Tony shared how we're helping companies turn volatility into a competitive advantage by grounding AI in "engineering truth" rather than statistical guesses. Key takeaways from the keynote: ✅ The comprehensive digital twin: Connecting mechanics, electronics, and software into one shared, real-time picture ✅ Data fidelity: Why Teamcenter X is making AI accessible for businesses of all sizes ✅ Trusted outcomes: Moving from "design to cost" to "design to source" in seconds Whether it's stacking 200 billion transistors on a chip or optimizing a Gatorade production line, the goal is the same: faster engines, smarter execution, and trusted outcomes.

Reliability engineers in the aerospace and defense sectors often face a frustrating bottleneck: valuable system information already exists, yet reliability models are still being built manually from disconnected spreadsheets and technical docs. This duplicated effort doesn't just drive up costs—it creates a gap between the reliability model and the actual product definition. By leveraging the MBSE digital twin already managed in Teamcenter, organizations can finally close that loop. Connecting SysML-based system models with Simcenter MADE allows for a seamless flow of data, ensuring reliability analysis is synchronized with the latest design and configuration. The impact is measurable. As James Hill, CEO of SkyPath Analytics, notes, this model-based approach can make FMEA updates 50% faster and significantly cheaper than traditional methods. It’s about shifting reliability analysis earlier in the development cycle to support better design decisions and a stronger digital thread.

You've seen robot dogs as examples of autonomous technology for industrial operations, but have you seen what happens when you add a few legs? 🪲+🤖= ❓ Hexapod robots are an up-and-coming advancement in leg-based robotics that offer stability, the ability to navigate environments big, small and irregular and solutions for inspection and exploration applications. To create each of these legged robots, engineers need to manage a complex combination of mechanical design, actuation systems, controls, software, sensors, power management and AI. Many are taking a model-based approach using products like our Simcenter Amesim mechatronic systems simulation platform to: 🌐 Replicate real-world environments to test operations reliably, safely and efficiently ✅ Evaluate, optimize and validate robot architectures before building hardware ⏱️ Run variables for physics-based tests in seconds versus hours 📊 Reduce costs and identify potential errors faster without physical prototypes Learn more about these innovations at our blog: https://sie.ag/5BfoPj

Reusable spacecrafts offer more sustainable, cost-effective and reusable materials for aerospace innovation but also challenge engineering teams to work on more complex designs across multiple disciplines. 🚀🌌🛰️ A recent example came from The Exploration Company, a developer of reusable, launcher-agnostic space systems, which reported its engineers progressed an orbital demonstration capsule from concept to flight hardware in just nine months. How? By integrating our Teamcenter software into engineering environments powered by Designcenter software, Simcenter software, Capital software and more from Siemens Xcelerator to: 🔁 Connect mechanical, electrical and simulation engineering environments 1️⃣ Create a single source of truth for better collaboration and data management 👀 Increase visibility and throughout the development process ✅ Establish digital threads across lifecycles for consistent alignment during development and validation stages Learn more at the blog: https://sie.ag/615QNd

Three German engineering students saw a problem: cheap, autonomous drones are becoming easier to build and deploy—and the leap from battlefield to civilian airspace is already happening. So they started Daedalus Defense. Instead of knocking hostile drones out of the sky overcrowded spaces (which risks debris falling on people), their interceptor deploys a patented folding net mid-flight, captures the target, and carries it safely away. The net drops afterward. The drone flies again. Reusable. Practical. What started as a university business challenge in October 2025 is now becoming real hardware—iterated through Solid Edge CAD, tested in 3D-printed prototypes, and refined through actual flight testing. This is how innovation works: engineers with an idea, tools that scale their capability, and partners who understand that speed in a critical moment means everything.