Designing for manufacturability (DFM) is the creation of products that are functional and efficient to produce. This requires close collaboration between design and manufacturing teams and tools that make the process seamless. An essential element of this workflow is ensuring that designs are clear and production-ready.

Manufacturers rely on 2D CAD to translate complex ideas into straightforward technical drawings with accurate measurements and instructions. This makes it easy to communicate ideas with minimal effort. A well-prepared 2D plan reduces production risks and saves both time and resources. The straightforward nature of 2D CAD helps accelerate design cycles and improves coordination between teams.

When needed, 2D CAD can also integrate with 3D modeling software. Designers can start with a 2D layout and use it as the basis for creating 3D models in tools like SOLIDWORKS. This approach maintains consistency and allows smooth transitions between formats.

For additive manufacturing projects, the role of 2D CAD is just as critical. Even though 3D printing starts with a 3D model, the design process often begins with 2D layouts and technical drafts to establish accurate dimensions and details. This ensures the model is well-prepared for printing and enables quick iterations, reduced material waste and efficient prototyping.

2D CAD tools also support the development of complex geometric parts that traditional subtractive methods struggle to produce. Internal cooling channels or lightweight structures can be outlined in 2D and then translated into a 3D model for printing. The flexibility of 2D CAD, combined with the layer-by-layer approach of additive manufacturing, makes it possible to create intricate designs while streamlining the production process and minimizing errors — all without requiring multiple software platforms.

Effective design for manufacturability relies on clear communication between engineering and manufacturing teams. Teams can work together without barriers by using standard file formats and ensuring smooth data exchange between software like SOLIDWORKS or CATIA. This compatibility reduces errors and helps everyone stay aligned on the same design — avoiding costly delays and rework.

Collaboration between design and manufacturing teams is critical. Cloud-based CAD platforms offer flexibility and make it easy to share files and revisions in real time. This shared environment simplifies the handoff process and ensures everyone is working with the latest version of the design. When design changes are made, they are reflected across all associated files, keeping the project on track and preventing misunderstandings during production.

Best practices for optimizing designs for manufacturability include:

1. Prioritize clear documentation and communication. Use 2D CAD to produce detailed technical drawings to communicate design intent to manufacturing teams. This minimizes misunderstandings and ensures everyone has the correct information.
2. Leverage 2D CAD as the foundation for design. Begin with a well-prepared 2D layout to establish accurate dimensions and specifications before transitioning to 3D modeling. This approach helps maintain consistency and ensures that all necessary details are included early in the design process.
3. Integrate 2D and 3D workflows. Utilize 2D CAD as a starting point for 3D designs, creating a smooth transition between formats and enabling better collaboration across platforms like SOLIDWORKS or CATIA. This integration simplifies modifications and keeps designs consistent, from 2D sketches to 3D models.
4. Use standard file formats for seamless collaboration. Ensure that all design files, whether 2D or 3D, are compatible across different CAD platforms. This makes it easier to exchange data between teams and reduces errors caused by file conversion issues, enabling smoother collaboration between design and manufacturing.
5. Adopt cloud-based CAD tools for real-time collaboration. Implement cloud-based CAD solutions to enable real-time file sharing, version control and seamless updates across teams. This ensures everyone works with the latest design version, reducing delays and simplifying the handoff process between design and manufacturing.

For those looking to optimize their engineering workflow, DraftSight provides powerful 2D CAD tools that connect with platforms like SOLIDWORKS and CATIA. In traditional manufacturing, or new techniques like 3D printing, DraftSight helps ensure your designs are straightforward, production-ready and easy to share. Try DraftSight yourself with a 30-day free trial.

The post 6 best practices to optimize engineering designs for manufacturability appeared first on Engineering.com.

Sure, it might be the most common answer to questions about the best 3D modeling software for beginners, but you’re not a beginner. You’re an engineer, and even if you’re just getting started with CAD software for 3D printing, you’ll need a feature-rich application that’s powerful as well as accessible.

So, here’s a list of five (mostly) free design tools you can use to get started in 3D printing.

Blender

Blender is a free, open-source 3D graphics software that’s used to create animations and visual effects as well as 3D models. This broad functionality gives it a relatively steeper learning curve compared to some of the other items on this list, but that also means it can be very useful once mastered.

While it’s not primarily CAD-focused, Blender is useful for creating organic shapes and it has a 3D printing toolbox extension that can calculate mesh volume and surface area, as well as check for bad geometry. There’s no formal support line, but its large community of users has created plenty of online tutorials for beginners. Blender software runs locally but files can be shared and collaborated on using cloud storage services.

Fusion

Autodesk Fusion is a CAD, CAM and CAE tool that combines industrial and mechanical design, collaboration, simulation and documentation. In terms of its learning curve, this software sits roughly in the middle of our list: more beginner-friendly than some CAD software, but it still takes time to master, especially the more advanced features.

Fusion is free for personal use, as well as for students, with paid subscriptions for commercial use starting at $85/month. In addition to Fusion’s large user base, Autodesk provides professional support for it, including official tutorials. The software operates on a hybrid model, with both cloud-based and local options, along with built-in cloud storage and collaboration features.

Onshape

PTC’s Onshape is a fully cloud-based CAD software with built-in version control and collaboration tools. It’s relatively easy for beginners and its cloud functionality helps simplify accessing and collaborating on designs. It also utilizes an open-source programming language called FeatureScript that allows users to create custom features.

Onshape is free for personal use, with subscriptions for commercial use starting at $1,500/year for each user. Its professional support is comparable to the other private offerings on this list, with numerous tutorials and forums, though the overall size of the community is somewhat smaller. The software’s biggest appeal is probably its extensive use of cloud computing, which reduces local demands on rendering and removes the burden on users to keep it updated.

OpenSCAD

Described as “the programmers’ solid 3D CAD modeler,” OpenSCAD is free and available to download for Linux, Windows and macOS. What sets it apart from Blender is its script-only modeller that uses a custom language. This means users can create 3D models in OpenSCAD, but they cannot interactively modify them in 3D. Instead, the software acts more like a 3D compiler, one that gives users full control over the modeling process.

Like Blender, OpenSCAD can have a relatively steep learning curve, though it’s much easier for those with previous coding experience. It also has no official customer support, and its community, although highly engaged, is relatively small. One particular benefit of OpenSCAD in the context of 3D printing is its ability to integrate with online model customization services, such as the Customizer tool on Thingiverse.

SelfCAD

SelfCAD is a cloud-based CAD software that can run in a browser or locally as a downloadable application for Windows or macOS. Created with beginners in mind, it’s probably the easiest to learn of any item on our list, though it also has some more advanced tools for freehand drawing, polygon reduction and Boolean operations. It’s also notable for having a built-in slicer, though in terms of features it’s still the most limited.

The software is free for basic use, with premium plans starting at $14.99/month or $139.99/year. SelfCAD has professional support, including an online Help Desk, as well as interactive tutorials and an active user community. Think of it as Tinkercad for big kids.

Looking for a more comprehensive list?

Consult our overview of software options for additive manufacturing design.

The post Top 5 beginner-friendly 3D printing design tools for engineers appeared first on Engineering.com.

The general sentiment around the usefulness of artificial intelligence (AI) has seen it’s ups and downs over the last couple of years. After bursting into public consciousness in late 2022, the hype has subsided. As we enter the final stretch of 2024, the current thinking is that AI is in bubble territory and companies should be wary of putting too much stock into its potential.

This is sound advice, no doubt. But as with any burgeoning tech, the early value is often found in the margins, helping companies gain an edge rather than bringing groundbreaking change. This holds true with AI—it won’t change society as we know it, at least not yet. But when applied to the right niche it could have significant impact.

The U.S. manufacturing sector, which was estimated to be worth about $2.5 trillion in 2022 by the National Association of Manufacturers, is one such niche that could reap significant rewards from a thoughtful and intentional approach to investing in AI.

First off, AI in manufacturing isn’t new, it just goes by a different name—machine learning. Secondly, much of the AI-based functionality being developed for manufacturing is done by major companies with well-funded R&D divisions and a strong foothold in the manufacturing market.

Indeed, virtually all of the major design software firms are finding ways to incorporate generative AI and large language models (LLMs) into their products. One such example is Boston-based software developer PTC’s cloud CAD system Onshape.

We caught up with Onshape’s CEO Jon Hirschtick to talk about its entry into the AI playground, how AI can bring value to manufacturers and what he sees in the near future for the still nascent technology. This interview was edited for clarity and conciseness.

Eng.com: How is PTC approaching AI technology?

Jon Hirschtick (JH): PTC is doing a lot with AI. We shipped some AI-based functions in our products and have a bunch of exciting AI-based projects under development, such as Onshape AI Advisor. We’re also active in the research community, where PTC employees are involved in research papers that are public. Our tools are being used by the AI community, perhaps even more than any other tools in our industry, for AI research. That’s another exciting dimension. There’s a ton of work and applications happening, and I’m proud that PTC isn’t getting overly hyped about AI, pushing things out before they’re ready. We’re focused and taking a solid approach.

Eng.com: So, at IMTS, you announced the Onshape AI Advisor, which is essentially an AI CAD assistant. Can you tell me why AI is a good fit for this application?

JH: With the Onshape AI Advisor, we’re using AI to provide expert user advice for fairly complex questions about how to use Onshape. These are the kinds of questions users typically ask another user or contact support or technical services. Instead of that, they can type a plain English question, even one that’s sophisticated, and get an answer about how to use a particular technique. AI is really good at this kind of task. It’s not rocket science anymore—it’s clearly within the wheelhouse of AI. This is very valuable for our users. We have deep professional CAD and PDM capabilities, and this is another layer of assistance.

Eng.com: Just to clarify the Onshape AI Advisor—is it a Q&A tool for users, or are you moving toward AI generating designs or doing the grunt work?

JH: It’s more than just an FAQ. It’s a conversational tool—you can ask questions, and the AI helps you with specific tasks, not just pre-set answers. As for generating designs, we’re working on it, but it’s not quite there yet. We’ve got great demos and research, but generating robust 3D geometry for manufacturing is still too complex. In entertainment, sure, you can generate digital assets, but for industrial applications, it’s not ready yet. There are too many safety concerns and error possibilities right now.

Eng.com: How long ago did you identify AI as something that needed to be developed for your product, your company and your users?

JH: It depends on how you define AI. If you define AI as machine learning, I’d say it goes back more than five years, when we started using machine learning to understand customer satisfaction through behavior. As for generative AI, almost from the moment it became known in research, we were involved in research papers, not necessarily knowing whether it would turn into real products. We had many people in the AI research community saying Onshape is the perfect platform for AI research because we’re the only cloud-native CAD and PDM system. Everything’s available through a REST API, so you don’t have to install a lot of software for large-scale usage, and with the right license agreement, you can access our public data library. Some people want to train on that 15 million human-created CAD and PDM documents. So, the research interest and commercial application started almost from day one. Over the last year or two, we’ve realized we could actually start shipping some of these things.

Eng.com: Absolutely. Your trajectory here matches many others who have integrated AI into their products. Can you talk a bit about the importance of further developing this and creating a baseline of AI capabilities to build on?

JH: I think it’s important that we explore what AI can do, and start shipping these products to customers because it’s new tech. I think AI is critical. I think our users must feel like product developers did when plastics or carbon fiber came along. It’s not just a better way of doing things; it’s a whole new set of tools that make you redefine problems. It allows you to approach problems differently. And so, the baseline is important not only for study but for releasing products. Just like with the first plastic product, you can’t know what it’s really like until you use it. We need to build reps, understand how to deliver and leverage the cloud-native solutions of Onshape.

Eng.com: The way you describe the Onshape AI Advisor brings to mind the concept of tribal knowledge within an organization. For years, we’ve talked about how companies lose access to knowledge due to retirement or attrition. This seems like a repository for that knowledge. It learns what people are doing and stores it for future users, correct?

JH: Yes, but it’s only a partial step. The AI assistant can give access to knowledge that a user might have taken with them when leaving the organization, so it helps there. But we’re far from tackling the whole problem. In the future, we might be able to develop a model specific to a company’s use of Onshape. Right now, the AI assistant only looks at general Onshape user knowledge—it doesn’t look at your specific data. But eventually, we could create a model around your company’s practices and provide insights like, “Here’s how experts in your company apply this technique.” So, it’s a partial step in that direction, but there’s a lot more we can do. We’re starting with Onshape AI, and there are other PTC products, like ServiceMax, which are also capturing expert knowledge.

Eng.com: It sounds like what you’re describing is essentially custom AI agents for a customer. Is that something on the horizon?

JH: Possibly. We’re not announcing anything yet, but if you ask me to speculate, I’d say it could definitely be part of our vision. PTC has a real leg up here, given our cloud-native infrastructure and the highly secure services we operate. We’ve been doing this for a while with Onshape and our PDM systems. So yes, we could imagine something like a custom AI agent for a company, where the AI looks at the best users in the company and helps new users align with those best practices. That’s something we could do in the future, based on the data we collect. It could be something like “What’s the best way to apply this technique in our company?” AI could inform decisions based on data, helping save time and improving efficiency.

Eng.com: AI agents are slowly becoming a thing for companies, but you need sensors and other devises to collect data for the agent. Is there a way around that that?

JH: With Onshape, we don’t need to go through that manual process of collecting data. Our system captures every single action as a transaction—if you drill a hole, undo it, or modify a feature, that’s all tracked. We have more data than any other system about a user’s activity, so we don’t need to go out and collect data manually. This gives us a huge advantage in training AI applications. In the future, users might even be able to combine data from their channels, emails, and other sources, and create a composite picture of what’s happening. We’re working on ways to give more value without relying on the kind of manual collection you mentioned.

Eng.com: Another PTC product named Kepware is a software layer that collects and aggregates shop floor data. Is this something you’re planning on incorporating into your AI products in the future?

JH: I can’t announce anything specific at the moment, but Kepware is well-positioned for this and there’s definitely potential there. Kepware handles sensor data, and we handle digital data from our systems. Combining those sources could be very powerful. The point is that PTC is uniquely positioned with both Onshape and Kepware, which span the digital thread spectrum. We’re also working with ServiceMax, which collects a lot of field service data, and they’re looking into AI for capturing service expertise as well.

Eng.com: Moving on to AI and digital transformation—what have you learned about AI’s application in manufacturing while attending IMTS 2024?

JH: At IMTS, I learned that we’re still in the early days of AI in product development and manufacturing. The promise is huge, but most organizations aren’t using a lot of AI yet. That being said, the number of projects people are working on is incredible. Everyone’s still figuring out which use cases work best, balancing doability, usability and value. I saw companies using AI in some exciting ways, like summarizing manufacturing data or configuring industrial products, but the technology isn’t fully ready for more complex tasks yet. I think the next few years will be about figuring out what works and refining those applications.

Eng.com: Do you think smaller companies are adopting AI faster than larger ones?

JH: Absolutely. The smaller companies tend to be more agile, and AI doesn’t necessarily require a huge investment in hardware or infrastructure. With Onshape and the AI assistant, you don’t need big machines or complicated installations. Smaller companies can jump in and take advantage of the latest tools without needing millions in capital. They’re moving faster in many cases, though not always.

The post Applying AI in manufacturing: Q&A with Jon Hirschtick appeared first on Engineering.com.

And debuting alongside Solid Edge 2025 is Solid Edge X, a new cloud-based, software-as-a-service (SaaS) version of the CAD application. It fits into Siemens’ growing portfolio of cloud-based engineering software that it calls Xcelerator-as-a-Service (XaaS).

So what’s the difference between Solid Edge 2025 and Solid Edge X, and what new features can Solid Edge users expect from each? To find out, Engineering.com spoke with Dan Staples, vice president of R&D at Siemens Digital Industries Software.

What’s the difference between Solid Edge X and Solid Edge 2025?

Like many of Siemens’ XaaS offerings (though not all), Solid Edge X is a cloud-based alternative to an existing desktop product—Solid Edge 2025. There are differences between the two products, but users of one should find the other largely familiar. “Core CAD is virtually identical,” Staples said.

Also identical is that both Solid Edge 2025 and Solid Edge X are accessed through desktop applications. Solid Edge X is not a browser-based app, nor is it a thin client that uses cloud computing resources—it’s a desktop program that “provides a simplified IT approach with centralized cloud license management, configuration and updates managed by [Siemens],” according to the Solid Edge website.

One of the big differentiators for Solid Edge X is that it comes with built-in data management based on Siemens’ popular Teamcenter PLM system. A derivative of Teamcenter called Teamcenter X Essentials is included with Solid Edge X, so users can get a running start on data management and won’t have to buy or configure any extra software to do so.

Another difference between the two versions of Solid Edge is that Solid Edge X has some extra AI functionality—most notably an AI-powered chatbot that aims to make it easier for users to find information and assistance from around the web.

“Sometimes it’s hard to know where to go to look to get a piece of information,” Staples said. “[The chatbot] will pull it all into a nice, concise, English bit of information for you.”

Staples says that AI is a big investment area for Siemens and that other AI features could be coming soon. He hinted that, like the AI chatbot, future AI features may remain exclusive to Solid Edge X.

Pricing and licensing of Solid Edge X and Solid Edge 2025

What about pricing and licensing?

Solid Edge X is SaaS software, so it’s a subscription by nature. It’s got named-user licensing and is available in three tiers: Standard, Advanced and Premium. Solid Edge 2025 is available either as a subscription, with both node-locked and floating licenses, or as a perpetual license with optional maintenance, and is also offered in tiers of increasing functionality.

Though pricing will vary by region, Staples said that Siemens aims to keep the prices comparable between the two versions of Solid Edge. At time of launch, in the U.S., here’s how the pricing compares:

Both versions of Solid Edge will support value-based licensing, an option that Siemens introduced with the Solid Edge 2023 release.

Value-based licensing lets users spend tokens to rent add-on software as needed. For example, a user with 25 tokens could use 10 of them to access generative design, 10 to access point cloud visualization and 5 to access simulation (these values are made up for the sake of example). If the user no longer needs generative design, they can trade it back for 10 tokens to use on another add-on product.

With the 2025 release, Solid Edge now has access to several new add-ons (see image above), and Staples says the options will continue to expand.

What’s new in Solid Edge 2025?

The latest update to Solid Edge brings a typical flurry of performance and productivity enhancements, a full rundown of which you can find in Siemens’ Solid Edge 2025 introductory video.

One of Staples’ favorite updates is the new quick pattern command, which allows users to create geometry patterns without creating extra sketches. Functionally, quick pattern takes a piece of Solid Edge’s Synchronous Technology and brings it to ordered modeling.

“We’re taking concepts that we built for Synchronous and moving those into the history-based environment as well,” Staples said. “So now history-based does this super-fast, easy UX for patterning.”

Longtime Solid Edge users may also appreciate the new bend and etch features in sheet metal design. The 2025 version supports bend deduction and bend allowance from linked gage tables, with options including the ability to specify the bend calculation method. With improvements to wrap sketch, Solid Edge 2025 also supports precise etching across bends.

Other noteworthy updates include improved assembly performance (assemblies managed by Teamcenter will open up to 50% faster), a new style picker (akin to a color picker) that will make it easier to create and apply face styles, and an updated user interface with enhanced context toolbars and more personalization options.

You can learn more about Solid Edge 2025 at Siemens.com.

Update (October 24, 2024): The section on pricing was updated to include newly available price data.

The post Siemens debuts cloud-based Solid Edge X alongside launch of Solid Edge 2025 appeared first on Engineering.com.

Developers, however, can start to blend the physical and digital realms via technologies like virtual reality (VR), augmented reality (AR) and mixed reality (MR) — collectively referred to as extended reality (XR). But this dream is still in its infancy. As a result, developers need guidelines to ensure they are going down the correct path when creating XR experiences.

In this 7-page ebook, developers will learn:

• How XR is bound to change industry.
• Which challenges exist when making XR experiences for industry.
• Six best practices to keep the development of industrial XR experiences on track.
• How Unity can help make industrial XR experiences a reality.

To download your free ebook, fill out the form on this page. Your download is sponsored by Unity Technologies.

The post 6 Best Practices When Developing XR for Industrial Applications appeared first on Engineering.com.

Take Project Bernini, the 3D object generator that Autodesk unveiled earlier this year. Seemingly every speech by an Autodesk executive made mention of Bernini, suggesting it demonstrates the potential of AI to revolutionize design and manufacturing. But always with a tantalizing caveat: Bernini is just a proof of concept, not yet ready for commercial use.

Oh well. The most ambitious applications of AI may remain out of reach, but that doesn’t mean it’s not making a difference for engineers today. To prove it, Autodesk unveiled three new AI-based features for Fusion that are already ready (or will be soon): AutoConstrain, Automated Drawings and Autodesk Assistant.

Fusion AutoConstrain

Fusion’s new AutoConstrain feature uses AI to automatically suggest sketch constraints like symmetry, center points and all the other spatial relationships that Fusion users used to have to add manually. AutoConstrain will continuously evaluate the sketch and adapt the constraints to design changes.

Autodesk believes that AutoConstrain will save designers time in two ways. First, it will help them sketch quicker by eliminating the need to manually add constraints. Second, it will make their parametric models more robust, preventing errors and rework. Stephen Hooper, Autodesk’s vice president for design and manufacturing product development, says that it’s easy to overlook minor sketching inconsistencies that cause big problems further in the design process.

“If you’ve created a complex sketch and you don’t apply the constraints accurately, you can drag the sketch and everything turns itself inside out,” Hooper told Engineering.com. He provided the example of a square—or what the designer meant to be a square—that’s actually a sliver of a degree away from a true right angle, preventing proper alignment in an assembly later on.

“These little problems that sound mundane cause huge issues for customers when they’re working later on in the process,” Hooper said. “So automating that, and deriving those constraints for them so they’re 100% accurate every time, should be a big productivity boost for them,” Hooper said.

AutoConstrain will be available to Fusion users by the end of January 2025, according to Hooper.

Fusion Automated Drawings

Automated Drawings has been a feature in Fusion since January of this year, but Hooper says that Autodesk has now made it more intelligent with AI. It does what you’d expect: automatically generate drawings from a 3D model including 2D views, dimensions and other manufacturing details.

“AI doesn’t just generate the drawings; it intelligently decides what details are necessary and what can be left out,” according to the Autodesk blog post announcing the AI update. “For instance, it can identify fasteners or other components that don’t need to be included in the final drawing… The result is a streamlined drawing set that’s ready for manufacturing without the need for excessive manual revisions.”

Autodesk Assistant in Fusion

Autodesk Assistant will debut in Fusion’s manufacturing workspace. It’s a text prompt interface that Hooper describes as “manufacturing aware.”

The assistant can answer user questions like “How can I program my toolpath to avoid slot milling?” or “What manufacturing methods should I consider for this part?” and, according to a blog post written by Autodesk’s Jeff Kinder, executive vice president of product development and manufacturing solutions, “Autodesk Assistant will respond with Fusion-specific answers, or answers specific to manufacturing, and share hyperlinks to original sources.”

But it’s not just text in, text out. Users can give Autodesk Assistant commands relating to their part, and it will be able to call Fusion functions to accomplish the task.

“The output is actually a machining strategy or a 3D piece of geometry, so that’s a little different from a text assistant. It’s actually creating intellectual property for you,” Hooper said.

Like Fusion AutoConstrain, Autodesk Assistant in Fusion will be available by January 2025, according to Hooper. He sees great potential for the technology, which could evolve to accept voice commands and spread to other Fusion workspaces.

“It’s one of these things that looks understated when you see it, but I think the applications for it are quite profound,” Hooper said.

The post 3 new AI features in Autodesk Fusion appeared first on Engineering.com.

Why? In a word: Write.

In slightly more words, courtesy of Autodesk’s director of product management Bankim Charegaonkar: “We’re releasing the ability for people to write custom property data back to Fusion… just like Fusion created it natively.”

Engineering.com spoke with Charegaonkar to learn why that matters, who can benefit from it and what the Manufacturing Data Model API could eventually become.

The write stuff

Autodesk released the original Manufacturing Data Model API as a way for users to access the cloud data underpinning their Fusion projects.

“The data can be multifaceted between design, manufacturing, simulation, generative, etc., but it’s still working off of the same core thing, and that core thing is what we call the Manufacturing Data Model,” Charegaonkar explained.

That core Manufacturing Data Model is what users can access with the new API. Version one of the API offered only read access, allowing users to query their Fusion data without having to access it through the software. But for most who used the API, read access alone wasn’t enough. “The number one request,” Charegaonkar said, was that users wanted to write data back to the Manufacturing Data Model.

And now, with the Manufacturing Data Model API v2, they can. That’s good news for third party developers looking to integrate with Fusion in a bidirectional way.

“It could be a partner building a costing application, another one building supply chain integrations, building apps for integrating to ERP or MRP systems,” Charegaonkar said. “Now all of them can be built and they can react in a live way to what’s happening in Fusion.”

How far does the Manufacturing Data Model API go? Not all the way—yet. But it’s got plenty of power as is.

What can you do with the Manufacturing Data Model API?

The Manufacturing Data Model API gives users read and write access down to the component level in Fusion.

“You get the whole assembly structure, the material of every component, the B-Rep information for it, the mass properties, etc.,” Charegaonkar said. Users can also create custom properties to augment the data model however they like.

That level of detail is enough to facilitate interesting software integrations. Take OpenBOM, for instance, which used a beta of the new API to make its BOM workflows available inside Fusion and, conversely, enable its users to interact with Fusion data directly from OpenBOM.

“This integration promises to streamline workflows, enhance productivity, and make life easier for designers, engineers, production planners, supply chain, and procurement people,” said OpenBOM founder Oleg Shivolitsky in Autodesk’s press release.

However, there’s more detail that exists in the Manufacturing Data Model than is currently open to the API. As Charegaonkar looks to the future of the platform, he sees more and more of that detail becoming available. “As we continue to granularize that data further, you’ll see sketches and parameters and features,” he said.

The more detail open to the API, the more Fusion users will be able to take advantage of time-saving automation.

“So if you were cabinet manufacturer and you had your five key driving dimensions… you could interact with this API with a simple app [that] changed the parameters,” Charegaonkar said, suggesting that this could become an automated configurator to showcase customization options.

The future possibilities of the API are exciting. Charegaonkar suggested that it may move beyond design data and into manufacturing and simulation data as well, opening even more automation possibilities.

Accessing the Manufacturing Data Model API

A beta of the Manufacturing Data Model API v2 has been available since earlier this year. Now, the revamped API is available to all Fusion subscribers through Autodesk Platform Services.

“There’s a full framework there for how apps get developed, how they get released,” Charegaonkar said. Users can publish apps on their own or through Autodesk’s App Store. Unlike Fusion add-ins, which are unique to a given user’s Fusion environment, cloud apps are managed across an entire team’s environment. That’s because they handle information, like BOM data, that needs to be consistent across the board.

“This is kind of on a path to making the cloud a true collaborator for you in your design process,” Charegaonkar said.

The post Autodesk releases Manufacturing Data Model API v2 for Fusion users appeared first on Engineering.com.

Reorganizations, mergers, and innovation are opportunities to create new product parts, thus increasing costs to design, manufacture, test, source, and store the parts.

In addition, as a result of global disruptions, manufacturers report that supplier costs are rising, deliveries are delayed and suppliers are less reliable/predictable. This can drain revenue and profits.

Enhancing collaboration between Engineering and Procurement can help companies address these challenges.

Watch our webinar to see how NETVIBES solutions powered by data science and AI generate part procurement savings.

• Uncover the synergies between Engineering and Sourcing with the Dassault Systèmes 3DEXPERIENCE platform.
• Learn how to streamline your new component sourcing by leveraging all of your data with 3D and artificial intelligence technologies.

This on-demand webinar is sponsored by Dassault Systèmes.

The post Optimize Part Procurement & Generate Savings appeared first on Engineering.com.

Engineering.com sat down with Sappin to chat about Catia and how it’s evolving for today’s engineering challenges. He’s got grand plans for AI, a three-pronged approach to sustainable product design and a clear vision of the longstanding Catia brand—it’s no longer just for CAD, but for engineering at large, he says. Here’s why.

The following transcript has been edited for brevity and clarity.

Engineering.com: What excites you most about Catia these days?

Olivier Sappin: When I started it was really an exciting time. We were just working with Boeing to do a full digital aircraft, the 777, which was a complete digital twin. And at that time we decided not only to do engineering, but to expand on full PLM manufacturing. We decided that we would revolutionize the way people are doing product innovation.

Catia v5 was one of the first systems to enable our clients to capitalize their knowledge and know-how. And it resonates a lot today because the companies that work to capitalize all their knowledge will be the ones to take the most advantage of AI.

Without data, you cannot activate AI. ChatGPT works because it can run on billions of pages of text, images. You cannot find 3D assets on the web. You cannot type 777 and get the digital 777 because the IP is at Boeing.

So it’s a real advantage to have capitalized this knowledge and know-how. And that’s the main thing happening in Catia right now, to leverage artificial intelligence having the capacity to elevate our client’s data into real knowledge and know-how.

And by the way, this is why Catia runs on the platform. We are not running on files anymore, because the files are on everyone’s desktop or laptop and you cannot leverage them. So Catia on the 3DExperience platform on the cloud is definitely the way for our clients to get their data elevated to real knowledge and know-how that they can leverage for getting the most advantage of artificial intelligence.

Could you give any examples of how your customers have been able to use AI?

We’re actually working with key clients in the automotive, aerospace and other sectors. I can give you some examples but I cannot mention names at this point.

I’ll give you one typical use case. I’m working with a Japanese client and they want to automatically assemble all car components into a full virtual tree. And believe me, it still takes a lot of time. Let’s say engineers want to assemble a suspension. They need to take the spring of the suspension, the knuckle, the different parts. They need to get the knowledge about where this part is being assembled. They want to check new components, they want to validate the kinematics, they want to validate the NVH durability, they want to do a lot of simulation and it takes a lot of non value added tasks for them to rebuild that.

So with AI, we have been able to basically look after all the components of these clients and learn from past assemblies to automatically identify the functional area of the part, the one that helps to be connected to another part. And the system learns and automatically creates an assembly for the engineer. You can save a lot of time and you can imagine that with that you can potentially explore much more innovative ideas.

So it’s not only a time reduction, cost reduction, which is obviously an objective. But it’s also, within the same amount of time, how much space of possibility can you explore? To imagine, for example, a new car platform, to have an electric motor or battery and so on. And this is extremely helpful to accelerate innovation.

Another use case is to leverage natural language to interact with Catia. We think that asking direct questions to the system will be more and more common, so we are already testing about 50 to 60 different large language models to evaluate what would be the most beneficial to basically talk to Catia in natural language. So you can imagine that in the future you have a kind of assistant that will augment engineers.

How will that work? Instead of clicking and typing will users simply tell Catia to, say, sketch a circle with a diameter of 10 millimeters?

Yes, but not only that. We think that if we want to go to natural language, it’s not only to speak the language of the system. When you say please do me that sketch, it means you’re already a designer, because you know what a sketch is. And maybe some engineers don’t know what a Catia sketch is because they don’t know Catia.

So you potentially ask questions in the Catia language, but you would also be able to ask questions in the automotive language. ‘Please can you propose me a vehicle architecture that fits 5 passengers for a mid-size minivan in Korea?’

And so we will leverage the company know-how, but also what’s on the Internet. So, for example, you can find automotive handbooks, you can find regulations. If you want to develop a car for the U.S. market, for the dimensions of the car there are some boundary conditions to take into account which are declared in norms and regulations.

So AI will both use this type of regulation and academic knowledge plus the knowledge of the company, because each automotive OEM has developed cars for many years. So they also have their own expertise written in text, Excel spreadsheets or whatever. We will leverage both academic knowledge and client knowledge to give an answer into Catia in natural language.

We are not going to replace engineers, because the point is we are going to augment engineers. The differentiating point will be in the way people are looking at the answers, exploring different alternatives and making the right decisions. So we are not going to design cars with robots. We are going to augment the capacity of engineers to find the best innovation for the next vehicle.

What’s the projected timeline on the capabilities you’re describing?

We already have many AI technologies in our platform and solution. And I think progressively we are going to implement different capabilities starting next year.

Is Catia doing anything to aid sustainable product design?

Yes. There are three axes to this.

Sustainability for us starts with a very simple thing: improving product performance to get less emissions. For example, you reduce the weight of an aircraft, you reduce emissions. You improve the aerodynamics of a car, you reduce emissions. So the first thing we have done for many years is that we are helping our clients to improve sustainability goals by improving product performance.

That’s number one. Number two is we have introduced a specific dedicated product into Catia for LCA, lifecycle analysis. So it means that if you are an engineer, you can use this product to automatically generate the scorecard for where you are against sustainability goals.

We have been partnering with a company called Ecoinvent, which has the library of human activity that generates things that need to be reduced—so CO₂ emissions, water consumption, greenhouse gas, whatever.

So if you are a Catia designer, you know the product, you have a geometry, you have the material. So we are automatically able to compute a set of parameters to help clients to produce a lifecycle assessment of their product.

And it’s important to do this in Catia. If you do it after the fact in an Excel spreadsheet, it’s good you are reporting, but what we want is not to do reporting. It’s to be able to assess the lifecycle analysis early enough, at the concept stage, so that when you find that there is a problem, you can still solve it. If you discover it too late, maybe you will not be able to change the product or it will be so costly that you will never do it. So the more we can take that upfront, the more you can influence.

So that’s the second axis. The third axis is very interesting. When you do design for circularity, it’s a whole new approach. It’s a completely new way to do innovation. Because you really need to have in mind not only that the product will fit to the client or will be aesthetic or will have the right performance, you have to take into account how much it is circular.

And so we have put together a systematic approach, which means that even before you start creating 3D, you think about the requirement of the product, you think about the function, you think about the logical architecture of that product so that it’s circular from day one.

The system approach is very key in the future of Catia in what we do right now. Catia for many years has been seen as a CAD system to do parts in 3D. But the reality is that now products are more and more complex, the mix of mechanical, electrical, software. So if you want to be able to design such a system, you need to have a system approach. The market is calling it model based systems engineering, MBSE.

So Catia is not only a CAD system anymore. Catia is a tool for engineering at large that combines what we do best on 3D for the last 40 years plus the system approach. And this system approach is very clear for all. It is very critical for sustainability and circularity.

Thank you for taking the time to speak with us today.

My pleasure. There is a real revolution in our sector. The passion for engineering is in our DNA, and this is why we want to serve this market in the best way.

The post Catching up on Catia: AI and the three axes of sustainable product design appeared first on Engineering.com.

To make this easier for users, AutoCAD has a set of CAD Standards tools that help maintain consistency and adherence to company (or industry-specific) standards. Here’s how to use them.

Building your AutoCAD standard

Step one is building the standard. The CAD Standards tools rely on drawing standard files (.dws). These standards files are a special type of drawing with all the settings and styles of drawings minus the geometry.

As .dws files are drawings, you can start from scratch or save an existing drawing. You have control over what the standards define. Create standards for project or customer requirements, company guidelines or to match industry standards. AutoCAD checks layers, linetypes, and styles for dimensions, multileaders and text.

The drawing properties title and comments become the standards description and are viewable when attaching it to a drawing.

Configuring standards in AutoCAD

Configure Standards lets you associate drawing standards files with the current drawing. The .dws file acts as the reference for all standards checks and corrections.  

The description is information about the standards currently selected. This description is the title and summary set in the drawing properties of the standards file.

Use Remove (the X) to dissociate the file. This does not delete the file but removes it from the drawing.

As you can associate multiple standards, use the arrows to change the order. AutoCAD checks standards starting with the first in the list and works its way to the last. If the same style or layer exists in different standards, AutoCAD uses the settings of the first found.

AutoCAD adds a standards plugin for each standard object it checks. From the Plug-ins tab, you can turn off object types you do not want to check for in the drawing.

Use the settings to manage options for notifications and checking standards.

Notifications can be turned on or off or be set to display as an icon in the status bar. When set to Display Alert upon Standards Violation, AutoCAD shows an alert bubble as a standards violation occurs. As an icon, no notification bubbles pop up, but an icon appears in the status bar.

Enable the automatically fix feature for AutoCAD to correct non-standard properties without prompting. AutoCAD only fixes non-standard objects when the style or layer name matches one in the standard but the properties differ.

The standard used to automatically fix non-standard properties defaults to the first standard in the list. Alternatively, select the standard for AutoCAD to use from the Preferred standards list.

Checking standards in AutoCAD

Select Check Standards to compare the current drawing against the attached standards (.dws). You can also start it from the standards violation bubble notification.

The process flags property discrepancies found in layers, styles and linetypes against the standards. With each violation, you can fix it, mark it as ignored or select next to skip it and move on.

The problem describes the nonstandard object or property discrepancy. With non-standard objects the Fix button stays unavailable until you select a fix. To resolve the problem, select the replacement from the Replace With list and click Fix.

AutoCAD lists all possible replacements for the current violation; the recommended one (if there is one) is preceded by a check mark. The preview shows the properties of the non-standard object changing with the selected Replace With.

Select Mark This Problem as Ignored to flag the violation as confirmed. Use this when you accept the violation to not make any changes. This tags the violation with your name so others who may use the drawing do not fix the issue.

If the Show Ignored Problems option is turned off in the CAD Standards Settings, ignored problems are not displayed the next time the drawing is checked.

Select Settings to access the CAD Standards Settings dialog.

Layer Translator in AutoCAD CAD Standards

The Layer Translator transcribes the drawings layers to another layer set. This is useful when collaborating with others or transitioning to different standards.  

The Translate From section lists the current drawings layers, those to be translated. The icons proceeding the layer name differ between referenced and unreferenced layers. You can delete unreferenced layers (as they are not used) by right-clicking the layer and selecting purge.

Use Load to add the destination layer scheme. You can use a drawing, drawing template or standards file.

You can load layers from more than one file. If you load a file that contains layers of the same name as layers already loaded, the original layers are retained and the duplicate layers are ignored.

Select New to define a new layer. This layer appears in the Translate To list for translation. If you select a Translate To layer before choosing New, the selected layers properties are used as defaults for the new layer. You cannot create a new layer with the same name as an existing layer.

Typically, you start with Map Same. This matches the same named layers in both lists. The drawings layers properties change to match those of the matched layers in the Translate To list.

In the Translate From section select a layer or layers you want to translate. Then select the desired destination layer from the Translate To section. Pick map to perform the translation.

The Layer Translation Mappings section lists each layer to be translated and the properties to which the layer will be converted. You can select layers in this list and edit their properties using Edit.

With drawings with many layers, consider using the Selection Filter to quickly select layers based on wildcard searches.

Use Save to capture the current layer translation mappings to a file for later use. Select Translate to start the translation process.

Batch Standards Checker in AutoCAD

With the standalone Batch Standards Checker you can check multiple drawings for standards violations. This tool does not fix the violations but creates an HTML report summarizing the found issues.

Find this tool in the Start Menu in the AutoCAD folder. It is included with all flavours of AutoCAD, including AutoCAD Mechanical (shown in the image).

To run an audit, you require a standards check (CHX) file. This check file sets up the scan. Once created, you can reuse it in future scans.

To create the check file, start by selecting New. Then, from the Drawings tab, select the plus icon to browse for and select the drawings you want to check. You can repeat this process to select drawings from different folders.

AutoCAD scans the drawings in the listed order. Use Move Up and Move Down to reorder the drawings. Use the X to remove selected drawings.

Enable Check external references of listed drawings to include found XRefs and scan them for violations.

By default, the Batch Standards Checker checks each drawing against its associated standards files. Use the Standards tab to change this default and add standards files. The checker then uses the assigned standards, ignoring all associated standards contained within the drawings. You also want to do this when there are no standards associated with the drawings.

When adding multiple standards, the order sets the precedence, with the top one taking the highest priority. Use Move Up and Move Down to rearrange the order.

With the Plug-ins tab, you can disable standards from being checked. For example, turn off Linetypes so the scan does not look for linetype violations.

Use the Notes tab to include comments in the report.

From the Batch Standards Checker toolbar, click Save to save the current standards check file or Save As to create a new check file.

With the check configured, select Start Check from the tool. This starts the scan against the loaded drawings. The Progress tab shows summary information about the scan status.

After the batch standards audit is complete, you can view an HTML report with details of the audit. You can also create notes that are included in the HTML report. This report can be exported and printed. In a collaborative environment, you can distribute the report to drafters so that they can fix any problems with their sections.

In summary, the standards tools within AutoCAD offer a mechanism for enforcing consistency, improving collaboration and enhancing the overall quality of your CAD drawings.

The post How to use AutoCAD’s CAD Standards tools appeared first on Engineering.com.