Mechanical Engineering CAD Models

Boosting SOLIDWORKS Assembly Performance: Turning Laggy Models into Smooth Workflows If you’ve ever worked with large assemblies in SOLIDWORKS, you’ve probably said this before: ➡️ “My assembly takes forever to load and is laggy when rotating or creating mates.” Recently, I worked with a client who had a 1000+ part machine assembly (and in many industries, assemblies can exceed 3,000+ parts). ⏱️ It was taking 4+ minutes to open, and every move felt painfully sluggish. Instead of upgrading hardware, we focused on workflow-driven optimization techniques inside SOLIDWORKS: ✅ Sub-assemblies – Grouped related components logically, reducing top-level mate complexity. ✅ Lightweight components – Loaded only the data needed in memory, improving responsiveness. ✅ SpeedPak configurations – Retained only essential faces/features for referencing while suppressing the rest. ✅ Simplified mates – Replaced high-cost mates with simpler reference-based constraints. ✅ Defeatured vendor models – Removed unnecessary details (threads, fillets, logos) from supplier parts. ✅ Large Assembly Mode – Applied automatic performance settings for smoother navigation. 🚀 The Result: Assembly now opens in 1.8 minutes (down from 4+). Navigation and mating are smooth and responsive. Bonus: BOM management and drawing creation became far easier. 💡 Key takeaway: Performance issues in SOLIDWORKS assemblies are usually workflow problems—not hardware problems. With the right methodology, you can transform a slow, frustrating model into a fast, efficient one. 👉 Have you faced challenges with large assemblies in SOLIDWORKS? Do you rely on workflow optimization or hardware upgrades? Let’s share best practices! Ekspe Software Services LLP Dassault SystèmessDassault AviationnDassault Systèmes Value PartnerssSolidWorks DesignerrSolidWorks FreelanceeSOLIDWORKSS3DEXPERIENCE Labb3DEXPERIENCE Eduu3DExperience platformm #SOLIDWORKSAssembly #CADPerformance #SOLIDWORKSTips #EngineeringProductivity #AssemblyWorkflow #LargeAssemblyMode #DesignOptimization #CADBestPractices #MechanicalDesign #ProductDevelopment #EngineeringWorkflow #SolidWorksPerformance #3DModeling #CADEfficiency #SolidWorks #dassaultsystem

CAD-CAE handovers are killing engineering speed. Not because engineers are slow. But because the workflow is full of friction. One team optimizes the geometry in CAD. Then the model moves to simulation. Then comes meshing. Then setup. Then monitoring. Then post-processing. Finally another design iteration. And the loop starts again. This is where weeks disappear. Not in the creative engineering work. But in the operational gaps between tools, teams and domains. For months, scientific publications have shown where this is heading: Multi-agent systems that design parts, generate meshes, run simulations and interpret results coordinated by an engineering orchestrator. Powerful idea! But often limited to open-source tools, Python libraries and research environments. Now this is moving into industrial practice. The team around Lucas Kempe (Aleksandar Trenchev, JAYAS P JACOB, Vipin Neekamparambath) at Accenture showed what this can look like when connected to real engineering toolchains. And they did not stop at CAD and CAE. They connected four industrial tools to an Engineering Orchestrator: 1. Siemens Polarion for ALM Requested changes are checked against requirements before execution.If a proposed design modification conflicts with requirements, the engineer is notified. 2. Siemens NX for CAD The part is created or modified directly in NX. Text-to-CAD instead of manual tool operation. 3. Altair HyperMesh for preprocessing The meshing agent prepares the simulation model automatically. 4. Altair HyperWorks for FEM simulation The simulation is started, monitored and evaluated. But here is the key point: This framework is not limited to these specific tools. It can be transferred to other engineering toolchains as well. The prerequisite is not a specific vendor stack. The prerequisite is that the tools expose the right API interfaces. That is what makes this approach so powerful. It turns existing engineering software into callable capabilities for agents. This is the important shift: The engineer does not disappear from the process. The engineer stays in the loop. After every agent call, approval is required. Responsibility and creativity stays with the engineer. Execution moves to the agents. That is the real promise of No-Click Engineering. Not replacing engineering judgment. But removing the repetitive work around it. The future of CAD-CAE workflows will not be defined by who clicks fastest through tools. It will be defined by who can orchestrate requirements, geometry, meshing, simulation and evaluation into one intelligent loop. Less waiting. Less handover friction. Less operational drag. More creative engineering work. That is where the productivity gain will come from. Tobias Regenfuss | Daniel Spiess | Tobias Geißinger | Nitin Ugale | Tracey Countryman

⚡️ 𝗦𝘁𝗼𝗽 𝗪𝗮𝘀𝘁𝗶𝗻𝗴 𝗧𝗶𝗺𝗲 on Manual CAD-BIM Checks! Automate Your Data Validation. Three years ago, checking just a couple of parameters in a Revit or IFC file could take hours — waiting for someone to open it in a vendor-specific tool, just to validate a few values. Today, you can do it yourself in a minute, and you don't need any special software. For too long, working with CAD-BIM project data meant juggling multiple programs and file formats, with manual validation slowing down every stage. But that’s rapidly changing. With open, automated pipelines, you can validate CAD-BIM data across all major formats — instantly and independently. Why you will end up using a pipeline: 1. 𝗨𝗻𝗶𝗳𝗶𝗲𝗱 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄: One process for all common CAD-BIM formats (RVT, DWG, IFC, DGN any versions) 2. 𝗢𝗽𝗲𝗻 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Built on n8n (open-source and offline) and Python — fully transparent, easily auditable 3. 𝗘𝗳𝗳𝗼𝗿𝘁𝗹𝗲𝘀𝘀 𝗰𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗟𝗟𝗠: Need to change a rule or automate more? Just ask ChatGPT or Claude to generate new code (upload an example of a finished workflow from our GitHub to the chat) — integrate it in seconds, with no vendor lock-in or “click-heavy” proprietary UI 4. 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗱𝗮𝘁𝗮 𝘀𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻𝘁𝘆: Yours data is yours, and you don't need to upload it to third-party storage or closed environments to work with it Remember when implementing IDS, BEP, or AIA requirements meant a ton of manual steps? Today, it’s just a few nodes in your automated workflow. If you want to see how it works, simply download the pipeline from GitHub and run the check in n8n within minutes. Try it now: 🔗 𝗚𝗶𝘁𝗛𝘂𝗯: https://lnkd.in/e5pFKYsz 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗡𝗼. 𝟯: n8n_3_Validation_CAD_BIM_Revit_IFC_DWG.json And we're opening up 𝗙𝗥𝗘𝗘 𝗔𝗖𝗖𝗘𝗦𝗦 𝘁𝗼 𝗮𝗹𝗹 𝗱𝗮𝘁𝗮 𝗰𝗼𝗻𝘃𝗲𝗿𝘁𝗲𝗿𝘀: ✅ Revit 2015–2025 (all versions supported) ✅ IFC (complete coverage: 2x3, 4.1–4.X) ✅ DWG files of all versions No more format barriers. 𝗡𝗼 𝗺𝗼𝗿𝗲 𝗳𝗼𝗿𝗺𝗮𝘁 𝘀𝗶𝗹𝗼𝘀: “I can’t open this CAD file” is now a thing of the past. No more version conflicts. Just seamless data extraction. This approach democratizes CAD-BIM data access across organizations, enabling project managers, QA teams, and stakeholders to verify deliverables independently. If you have any questions or need training for your team, please send me a private message. ♻️ Feel free to share this post with colleagues who are navigating the complexities of plugins and APIs just to work with CAD-BIM files. I’d love to hear your ideas or specific examples of use cases you would like to automate — share them in the comments or send me a private message.

Engineering Velocity: Reflections on Designing and Building Automotive Body Dies with Minimum Time and Cost After decades in tool engineering, I’ve learned that reducing die lead time comes from eliminating unpredictability across the classic workflow Design, Simulation, Machining, Assembly, and Tryout. When these stages act as a continuous process rather than isolated steps, both time and cost fall naturally. In design, stabilized geometry, controlled radii, and simplified addendum build the foundation for predictable forming. Excessive beads and over-correction might seem safe, but they usually turn into machining hours and extended tryout loops. In simulation, accuracy depends on disciplined inputs material curves, friction, binder pressure. A closed-loop cycle, where compensation updates flow directly into CAD and NC programming, prevents fragmentation and brings the die closer to its real forming behavior before steel is cut. During machining, multi-stage strategies and CAD-driven toolpaths tighten accuracy and cut rework. When the compensated model drives NC directly, machining becomes execution rather than interpretation. In assembly, modular interfaces standardized shoes, pillars, and pockets—reduce adjustment time and make the die’s mechanical behavior more predictable in spotting. Finally, tryout confirms the truth of every upstream decision. Press dynamics and material variability still require refinement, but when the digital preparation is coherent, tryout becomes calibration rather than rescue. Real reductions in time and cost come not from shortcuts, but from continuity when design, simulation, machining, assembly, and tryout reinforce one another with technical discipline and practical insight.

New research shows how machine learning can eliminate manufacturing bottlenecks by automatically recommending optimal production methods directly from CAD files. The AutoSplit workflow: 📐 CAD files (STEP format) from Fusion360, GrabCAD, TraceParts, etc. 🧠 CNN + MLP classification filter for standard parts 🧠 Random forest classifier for custom parts into AM/machining/sheet metal ➡️ Instant identification of appropriate manufacturing routes for both redesigns and new designs. Impact: 💭 Eliminates knowledge gaps between design and manufacturing teams ⚡ Accelerates development cycles through automated pre-classification 💰 Prevents costly manufacturing process selection errors 🔄 Enables hybrid manufacturing strategies for both new designs and redesigns