SOLIDWORKS Design vs Onshape: Which CAD Platform Is Right for Your Team?

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SOLIDWORKS Design vs Onshape: Which CAD Platform Is Right for Your Team?

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Choosing a CAD platform is a bigger decision than just comparing modeling tools.

Today, engineering teams need to think about collaboration, data management, cloud connectivity, licensing flexibility, training requirements, and even AI-powered productivity tools. Whether you’re replacing an older CAD system, evaluating cloud CAD for the first time, or planning for future growth, the platform you choose will impact your workflow for years.

Two of the most common options being evaluated today are SOLIDWORKS Design and Onshape.

Both are professional CAD solutions that support parametric modeling and offer cloud connected workflows. But they are built around very different philosophies.

Let’s break down the differences.

Quick Answer: SOLIDWORKS Design or Onshape?

If your team wants a mature, industry-standard CAD platform with powerful desktop performance, extensive engineering tools, flexible licensing options, and access to the broader 3DEXPERIENCE ecosystem, SOLIDWORKS Design is typically the stronger choice.

If your priority is a browser only CAD environment with simplified deployment and built-in cloud collaboration, Onshape may be worth considering.

The right answer depends on your team’s workflows, product complexity, and long-term goals.

What Is SOLIDWORKS Design?

SOLIDWORKS Design is the latest evolution of the SOLIDWORKS portfolio.

It combines the CAD environment engineers have trusted for decades with modern cloud services, collaboration tools, revision management, and AI-powered capabilities through the 3DEXPERIENCE platform.

Today, organizations can choose between multiple deployment approaches:

SOLIDWORKS Design Single-User License

A named-user license connected directly to cloud services and the 3DEXPERIENCE platform.

Benefits include:

  • Access from multiple devices

  • Built-in cloud collaboration

  • Cloud file and revision management

  • Continuous updates

  • AI-enabled cloud services and tools

SOLIDWORKS Design Device License

A machine-based license designed for organizations that prefer traditional deployment methods.

Benefits include:

  • Local installation control

  • Machine-based activation

  • Multi-user workstation environments

  • Optional cloud connectivity

  • Support for controlled IT deployment strategies

Both licensing options provide access to Cloud Services and future expansion into the broader 3DEXPERIENCE ecosystem.

Comparison of SOLIDWORKS Design and Onshape interfaces to help teams choose the right CAD platform.SOLIDWORKS CAD Modeling Environment

What Is Onshape?

Onshape is a fully browser based CAD platform.

Unlike traditional desktop CAD, there is no local installation. Users access their CAD environment through a web browser, and all data is stored in the cloud.

Because the platform is cloud-native, Onshape provides:

  • Real time collaboration

  • Built-in version history

  • Browser based access

  • Automatic updates

  • Simplified IT deployment

This makes it attractive for distributed teams, startups, educational institutions, and organizations looking to avoid workstation management.

Side-by-side comparison of SOLIDWORKS and Onshape highlighting key features for engineering teams.

Onshape CAD Modeling Environment

SOLIDWORKS Design vs Onshape: The Biggest Differences

Modeling Experience

Both platforms use modern parametric modeling workflows.

However, SOLIDWORKS Design still offers a more mature and feature rich modeling environment for many engineering use cases.

Areas where SOLIDWORKS continues to excel include:

  • Large assemblies

  • Weldments

  • Routing

  • Drawings and detailing

  • Manufacturing documentation

  • Simulation integration

  • CAM integration

  • Advanced surfacing workflows

For many engineers, SOLIDWORKS remains the benchmark for production ready mechanical design.

Onshape delivers a modern modeling experience and continues to evolve rapidly, but some organizations transitioning from mature desktop CAD environments may find certain advanced workflows less developed.

Performance

This is where deployment philosophy matters.

SOLIDWORKS Design

Most CAD calculations happen locally on workstation hardware.

Advantages:

  • Excellent performance on complex assemblies

  • Direct access to GPU resources

  • Better support for demanding engineering workloads

  • Less dependence on internet speed during modeling

Onshape

All modeling calculations occur on cloud infrastructure.

Advantages:

  • Lower workstation requirements

  • Easy access from almost any device

  • Consistent performance across users

For engineering teams working on large products, machinery, manufacturing equipment, or highly detailed assemblies, local workstation performance still offers significant advantages.

Data Management

Historically, data management was a major differentiator.

Today, the gap is much smaller.

Onshape

Includes cloud-based data management by default.

Users benefit from:

  • Version history

  • Branching workflows

  • Built-in collaboration

  • Cloud storage

SOLIDWORKS Design

Includes Cloud Services and can scale directly into the 3DEXPERIENCE platform.

Organizations can start with:

  • Share and Markup

  • Store and Revise

  • Collaborative Spaces

  • Cloud revision management

And later expand into:

  • Product lifecycle management (PLM)

  • Change actions

  • Governance workflows

  • Enterprise collaboration

This creates a growth path from basic collaboration all the way to enterprise level product development.

What About SOLIDWORKS xDesign?

This is an important distinction that often gets overlooked.

When comparing browser-based CAD, the most direct comparison is often SOLIDWORKS xDesign versus Onshape, not SOLIDWORKS Design versus Onshape.

SOLIDWORKS xDesign is Dassault Systèmes’ cloud-native design solution, running entirely in a web browser with no local installation required. It combines modeling, collaboration, lifecycle management, and cloud storage directly within the 3DEXPERIENCE platform.

Overview of SOLIDWORKS Design and Onshape showing differences in workflow and collaboration features.

SOLIDWORKS xDesign Modeling Environment

For organizations that like the flexibility of browser-based CAD but want to stay within the SOLIDWORKS ecosystem, xDesign is often worth evaluating alongside Onshape.

Many companies ultimately adopt a hybrid strategy:

  • SOLIDWORKS Design for advanced mechanical design

  • SOLIDWORKS xDesign for cloud-native collaboration and conceptual work

  • 3DEXPERIENCE for data management and lifecycle control

AI Features: SOLIDWORKS vs Onshape

AI is becoming part of every CAD discussion, but it’s important to separate practical tools from marketing buzzwords.

Neither platform has a “design my product” button.

Instead, both focus on productivity improvements.

AI in Onshape

Onshape currently offers AI Advisor, an AI-powered assistant designed to answer questions and guide users through workflows using Onshape documentation and training resources as its knowledge base.

AI Advisor can:

  • Answer workflow questions

  • Recommend best practices

  • Surface documentation

  • Provide troubleshooting guidance

  • Deliver contextual assistance inside the platform

Importantly, Onshape states that AI Advisor does not currently generate designs or make engineering decisions.

Visual comparison of SOLIDWORKS Design and Onshape focused on team collaboration and cloud capabilities.

Onshape AI Advisor

AI in SOLIDWORKS

SOLIDWORKS has been expanding its AI roadmap aggressively through both desktop and cloud-connected tools.

Recent AI capabilities include:

  • Auto-Generate Drawings

  • Command Predictor

  • Fastener Recognition

  • Assembly Performance Evaluator

  • Material Appearance Manager

  • BREP-to-Parametric CAD conversion

  • Design Change Impact analysis

  • PLM Model Insights

  • AURA AI Assistant

Rather than acting as a documentation assistant, many of these tools directly interact with engineering workflows and CAD data.

The goal isn’t replacing engineers. It’s reducing repetitive work, accelerating documentation, improving performance, and helping teams make decisions faster.

Illustration comparing SOLIDWORKS Design and Onshape to help determine the best CAD solution for design teams.

SOLIDWORKS AI Lab

Which Platform Is Better for Growing Companies?

This is often the most important question.

For startups prioritizing fast deployment and simple browser access, Onshape can be an attractive option.

For companies expecting growth, increasing product complexity, manufacturing integration, simulation requirements, or future PLM adoption, SOLIDWORKS Design often provides a more scalable path.

One of the biggest advantages of the SOLIDWORKS ecosystem is that organizations don’t need to commit to everything on day one.

You can start with:

  • SOLIDWORKS Design

  • Cloud Services

  • Basic collaboration

Then gradually expand into:

  • PDM

  • PLM

  • Simulation

  • Manufacturing

  • Electrical

  • Cloud-native design

  • AI-driven workflows

Without changing CAD platforms.

Why work with Solidxperts?

Choosing software is only part of the project.

Implementation, training, data management strategy, and user adoption are often what determine whether a deployment succeeds.

At Solidxperts, we work with organizations every day that are evaluating:

  • SOLIDWORKS Design

  • SOLIDWORKS xDesign

  • Cloud Services

  • 3DEXPERIENCE

  • PDM and PLM solutions

  • CAD migration projects

Whether you’re moving from another CAD platform, modernizing your data management strategy, or exploring AI-enabled workflows, our team can help you build a roadmap that fits your reality not just a software brochure.

The goal isn’t simply choosing a CAD tool.

It’s building a design environment that will still make sense five years from now.

Looking to go further?


Michael Habrich

3DEXPERIENCE Specialist

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    FAQ: AI at the Core of SOLIDWORKS and 3DEXPERIENCE

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    FAQ: AI at the Core of SOLIDWORKS and 3DEXPERIENCE

    What is AI in SOLIDWORKS?

    At its core, SOLIDWORKS AI refers to a set of intelligent capabilities that assist engineers by automating repetitive tasks, providing design guidance, and enabling workflow orchestration through built-in features and Virtual Companions that can be interacted with using natural language.

    What AI features are currently available in SOLIDWORKS?

    Currently, available capabilities include automated drawing generation, general design assistance through an interactive chat interface, command prediction, sketch analysis and repair, fastener recognition, and many additional features that are being rapidly developed and expanded.

    Learn more about what’s available in SOLIDWORKS AI.

    Stay up to date with the latest SOLIDWORKS Design features.

    What is the difference between built-in AI features and Virtual Companions in SOLIDWORKS?

    On one hand, built-in AI refers to machine learning-based capabilities that enhance existing design workflows. On the other hand, Virtual Companions are AI assistants that can be engaged using natural language to access knowledge and perform specific tasks. Both built-in AI features and Virtual Companions are available directly within the SOLIDWORKS Design user interface.

    What are the roles of the new Virtual Companions?

    Unlike generic conversational agents, our companions embody AI at the heart of engineering, grounded in physics and causality.

    Name

    Specialty

    Example Application (E-Foil Wing)

    AURA

    Knowledge and Context

    Balances requirements for strength, lightweight construction, and water resistance (for example, choosing between carbon fiber and fiberglass).

    LEO

    Engineering Reasoning

    Optimizes the strength-to-weight ratio using carbon composites, specifically unidirectional carbon fiber with epoxy resin for stiffness and fatigue resistance.

    MARIE

    Materials Science

    Analyzes critical factors such as density (1.6 g/cm³), elastic modulus, and resistance to water-induced degradation.

    How do these entities collaborate to optimize a project?

    Innovation emerges from the combination of multiple perspectives. AURA explores the range of possibilities, MARIE grounds the project in rigorous materials science, and LEO ensures mechanical and manufacturing feasibility. Together, they help identify the optimal technical solution without compromising safety or manufacturability.

    Why is the move to the Cloud essential for these new AI capabilities?

    Knowledge extraction, deep data mining, and the execution of complex AI models require significant computing power. Cloud infrastructure is the only practical way to provide these resources flexibly and cost-effectively to organizations of all sizes.

    Does SOLIDWORKS AI use customer data for training?

    No. Customer data is not used to train AI models. Governance controls ensure the protection of intellectual property. You can learn more by visiting the 3DS Trust Center.

    Can AI automatically create drawings?

    Yes. SOLIDWORKS Design includes the ability to automatically generate 2D drawings by interacting with Virtual Companions using natural language. Drawings can be created according to specified standards, templates, and dimensioning schemes, helping accelerate the documentation process.

    Can AI automate repetitive CAD tasks?

    Yes. SOLIDWORKS AI automates repetitive engineering tasks such as drawing creation and assembly structure generation. Additional capabilities will continue to be introduced in future releases.

    How does SOLIDWORKS AI protect intellectual property?

    SOLIDWORKS AI ensures that customer intellectual property remains isolated and secure. Learn more about the specific security protocols by visiting the 3DS Trust Center.

    How do I get started with AI in SOLIDWORKS?

    Start by exploring the built-in AI capabilities and current Virtual Companion features available through the AI Lab task pane directly within SOLIDWORKS Design. Access to Virtual Companions requires Cloud Services to be enabled, which are included with every SOLIDWORKS Design license.

    Can AI automatically fix CAD models?

    AI can identify issues, explain errors, and suggest corrections. However, engineers remain responsible for reviewing and approving any modifications.

    Will AI replace CAD designers and engineers?

    No. AI helps automate repetitive tasks and uncover valuable insights, but engineers remain responsible for design intent, validation, and decision-making.

    Want to Learn More?

    Discover more tips and tutorials on our YouTube channel.

    Explore best practices with our experts.

    Or contact our team, we’re here to help you get the most out of your platform.


    Benoit Bilodeau

    Senior Solutions Architect

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    Que vous soyez prêt à commencer ou que vous ayez quelques questions supplémentaires, vous pouvez nous contacter sans frais :

      3DDrive vs. 3DSpace: What’s the Difference?

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      3DDrive vs. 3DSpace: What’s the Difference?

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      The 3DEXPERIENCE platform includes a powerful set of tools designed to support collaborative product development. Two of the most commonly used apps for storing and managing files are 3DDrive and 3DSpace.

      At first glance, they can look similar, but they’re built for very different purposes. Understanding how each one is meant to be used will help your team work more efficiently and avoid confusion down the road.

      What Is 3DDrive?

      Think of 3DDrive as the 3DEXPERIENCE equivalent of tools like Dropbox or OneDrive.

      3DDrive allows you to:

      • Store and access files from anywhere

      • Edit and collaborate on documents in real time

      • Share files easily, including with external users

      • Integrate with other cloud storage services

      You’ll find 3DDrive under My Apps in the 3DEXPERIENCE platform, and it’s also accessible directly inside SOLIDWORKS.

      3DDrive interface in the 3DEXPERIENCE platform for cloud file sharing and management

      3DDrive uses a familiar folder based structure and focuses on flexibility and convenience. It’s a great choice for:

      • General file sharing

      • Early-stage collaboration

      • Working with customers, suppliers, or partners outside your organization

      What it doesn’t include is built-in product data management there’s no revision control, lifecycle states, or formal approval process.

      3DDrive interface in the 3DEXPERIENCE platform for cloud file sharing and management

      What Is 3DSpace?

      3DSpace is built for teams that need structure, control, and traceability.

      3DSpace interface in the 3DEXPERIENCE platform for product data management and revision control

      Instead of simple folders, 3DSpace is organized around Collaborative Spaces, where teams work together on shared project data. Within 3DSpace, you can:

      • Control access and permissions

      • Track revisions and history

      • Assign maturity states like In Work and Released

      • Lock files to prevent conflicting edits

      These capabilities make 3DSpace a strong foundation for PLM-driven workflows, including:

      • Engineering change processes

      • Approval workflows

      • Long-term product data management

      3DSpace is ideal for engineering teams that need confidence in version control and data integrity.

      3DSpace interface in the 3DEXPERIENCE platform for product data management and revision control

      3DDrive vs. 3DSpace: Which Should You Use?

      The short answer: it depends on how you work.

      • 3DDrive is best when:

        • You need fast, flexible file sharing

        • You collaborate frequently with external users

        • You want a familiar, lightweight cloud storage experience

      • 3DSpace is best when:

        • You need controlled access and revision tracking

        • Your team is ready for PLM-style workflows

        • Data accuracy, traceability, and approvals matter

      The good news is that both apps integrate directly with SOLIDWORKS, so you can access the right tool without leaving your design environment.

      Comparison between 3DDrive and 3DSpace in 3DEXPERIENCE showing file sharing and product data management

      Final Thoughts

      3DDrive and 3DSpace aren’t competing tools. They’re complementary. Many teams start with 3DDrive for simple collaboration and gradually introduce 3DSpace as their data management needs grow.

      Not sure which approach makes the most sense for your team? That’s where we come in.


      Michael Habrich

      3DEXPERIENCE Specialist

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        How SOLIDWORKS AI Is Being Positioned by Manish Kumar

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        How SOLIDWORKS AI Is Being Positioned by Manish Kumar

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        The Future of Work: Shifting from Automation to Value Creation

        In the age of AI, I am often asked: What is the true nature of “value”? For engineers, the pressure to reduce costs and optimize workflows is constant. Historically, we turned to simple task automation. Today, AI is shifting the focus from merely speeding up repetitive tasks to amplifying human ingenuity.

        Redefining Value in Engineering

        What is the real value of an engineer? It isn’t clicking a mouse to create a sketch; it is problem-solving and innovation.

        Consider a visit to the doctor. Is a doctor’s value found in typing notes into a chart, or in the focused diagnosis and long-term health planning they provide? Today, many doctors use specialized AI companions to handle transcription, allowing them to give patients their undivided attention.

        Similarly, an engineer’s value lies in ideation and rapidly converting concepts into virtual twins for experimentation. The manual steps—the clicks to create geometry—are a means to an end. While some fear AI will take away the “enjoyable” parts of CAD, we must ask: do you enjoy the manual execution, or the creative breakthrough? Automating the “busy work” of drawing creation lets us return to the reason we became engineers in the first place: creative problem-solving.

        The Human Role in an AI-Driven Future

        A common concern is that AI will replace human oversight. I strongly disagree. When designing a turbine blade or an aircraft engine, human validation is critical—lives depend on it.

        AI acts as a multiplier, not a replacement. If an engineer produces one design today, AI might help them produce ten tomorrow. This actually increases human responsibility. Engineers must review more outputs, ensure regulatory compliance, and make higher-level decisions. AI expands our capabilities, but it does not originate ideas. Just as AI image generators require a human prompt and refined intent, 3D CAD will always require human direction.

        This is the democratization of design. Thirty years ago, SOLIDWORKS brought CAD to every desktop, democratizing 3D CAD. Today, AI is the next wave of that movement, making 3D modeling accessible so more people can solve massive, complex problems.

        Embracing the Multiplier

        As I said at 3DEXPERIENCE World in February: AI is the engine; you are the driver.

        Professionals should never underestimate their worth. AI is a tool to unlock your potential, and the gap between early adopters and those who resist will only continue to grow. Learning to make AI work for you is the key to staying at the forefront of the innovation revolution.

        So, I ask you: which of your tasks could be delegated to agentic AI, or virtual companions, to help you better showcase your true value? I look forward to hearing from you and seeing what our future holds.

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          Why SOLIDWORKS Is Leading the AI Revolution in CAD

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          Why SOLIDWORKS Is Leading the AI Revolution in CAD

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           SOLIDWORKS and its parent company, Dassault Systems, have been ahead of the competition when it comes to all things AI. SOLIDWORKS started developing AI features, also known as Smart Features, decades ago, giving their software a lead above the competition. While continuing to invest and stay ahead of the pack, all new AI assistants are now directly available within the application, ensuring that integration is seamless.

          Follow along in this blog, because I want to show you all the amazing features SOLIDWORKS has already implemented over the year, along with what is in store for the future. By the end, I will have shown how the recent attempts of our competition’s software do not hold a candle to the advances SOLIDWORKS has already made, let alone what is in store for the future.

          Past Additions of Machine Learning and Artificial Intelligence

          For over a decade, SOLIDWORKS has been continuously adding features that make use of machine learning and artificial intelligence. From features such as Smart Mates or Smart Fasteners to new AI Drawing Creation, SOLIDWORKS has been working to optimize engineer time, and reduce the number of tedious repetitive tasks.

          Excelling in time optimization for years, SOLIDWORKS has continued making tools designed with engineering resources in mind. Tools like Fully Defined Sketch and Selection Accelerators have been available for years, helping make the sketching and selection processes faster. Always improving, SOLIDWORKS took the predictive selection accelerator from the Fillet command, and added it into Chamfers in recent years, making seamless group selection even easier than before in both features.

          Machine Learning and Artificial Intelligence

          Users can go from this underdefined sketch to this fully defined sketch in 3 quick clicks!

          Machine Learning and Artificial Intelligence 2

          There have even been productivity increasing tools in the assembly environment for just as long! Smart Fasteners and Smart Mates have allowed engineers to snap together parts and fill their holes with fasteners for over a decade. Even before the general public heard about AI and chatbots, SOLIDWORKS has been working to implement AI based features to improve the engineering experience.

          Current SOLIDWORKS AI Tool Additions

          In 2026, SOLIDWORKS continues this trend of improving the engineering experience through implementing countless new features in the most recent as well as future updates. Some such features include AI Drawing Creation, AI Assembly Creation, Automatic Fastener Recognition, Command Predictor, and Pattern Assistant, to name a few. With these tools, SOLIDWORKS will become even smarter, and can predict an engineer’s next move; whether that move is dropping a nut into place, or needing to add a pattern of bolts in one swift movement. SOLIDWORKS can now even assist engineers in making sure the most efficient patterning methods are being used, as an efficiency check to young engineers.

          SOLIDWORKS AI Tool Additions

          Tools, like Automatic Fastener Recognition, make use of a database of thousands of fastener files, allowing the SOLIDWORKS AI to determine if a part is a fastener as soon as it is dragged in to your current project. This recognition will allow the system to offer better mate conditions and groupings, for instance pairing a new nut to your existing bolt.

          Additionally, features like AI Drawing Creation and AI Assembly Creation take processes out of the engineers hands and begin these processes in the system background before bringing the engineer in for confirmation. From laying out standard views and annotations, to organizing folder structures in assemblies, SOLIDWORKS continues to assist in simplifying and standardizing these initial steps in creation and documentation.

          SOLIDWORKS AI Tool Additions

          With the use of SOLIDWORKS AI Drawing Creation, a simple conversation with LEO about the desired settings and defaults leads to a drawing created faster than ever before!

          SOLIDWORKS AI Tool Additions

          Addition of AI assistants in SOLIDWORKS

          SOLIDWORKS AI Assistants

          The most recent additions of artificial intelligence to SOLIDWORKS include the three all new AI assistants; AURA, LEO, and MARIE. Each serves a unique role throughout the CAD Design process, as described below.

          AURA is the starting point of any great project, even before you draw your first sketch. AURA holds the ability to leverage knowledge from both web and enterprise sources, making it your one stop shop for rapid confirmation. For questions regarding basic design rules and suggestions, or even searching your company’s knowledge base, AURA can answer it all.

          After the first steps with AURA are completed, LEO takes the reins. LEO can help users effectively solve many complications through the design process, helping validate your design and optimize your processes. Throughout both mechanical design, as well as simulation, LEO can take your prompts to generate assembly structures, as parametric features, run studies, and even help resolve design errors. For both answering questions, and offering solutions, LEO can solve many engineering headaches.

          The last assistant in the lineup is MARIE, your scientific research specialist. With expertise in materials science, chemistry and more, your thorough scientific research can be simplified. With this third member of the SOLIDWORKS AI trifecta, you have an assistant in your corner for every part of the engineering design process.

          Competitors attempts at replication

          Outside of SOLIDWORKS, many competitors have tried their hand in implementing AI for the benefit of users. While many companies have had good feature additions in recent years, it is hard to compare them to the decades of experience and additions seen in SOLIDWORKS. The following sections detail some of these features within the competing software, and shows how SOLIDWORKS has taken the lead in all things AI.

          For starters, Autodesk has invested in AI in Fusion 360. However, you will find no such features in Inventor. Looking into these, features like CAM hole recognition have existed in SOLIDWORKS for some time. The drawing AI tool seems to be in the early stages, having very little interaction or flexibility. Fusion can add relationships and dimensions automatically, much like Fully Define Sketch (something that has existed in SOLIDWORKS for nearly 20 years). The main hurdle that Autodesk will have to overcome is that their files don’t talk to each other, unlike the fully associative files found in SOLIDWORKS, making their AI feature development harder.

          Other competitors like Siemens have three main enhancements, Magnetic Snap, Automated Drawings, and a design copilot, all things that have existed or do now exist in SOLIDWORKS. Lastly, Onshape has a lot of potential due to their cloud-based nature, however the content released as of now is just in the infancy stage.

          The Bottom Line: SOLIDWORKS AI is Changing the Game

          After looking at the history of feature development, as well as a brief look at the competition, you can see that SOLIDWORKS continues to be designed with the engineer in mind. From features that increase productivity by decreasing repetition, to tools that give you a head start in the design process, SOLIDWORKS is a lifesaver. Many competitors’ Artificial Intelligence ambitions are just beginning, so SOLIDWORKS is working hard to maintain the lead they already have, while pushing engineering design technology to the next level. Our SOLIDWORKS Technical Team has been ahead of the pack when it comes to learning and using AI, so please contact us with any questions, and find out what makes us the Solidxperts.


          Alain

          Alain Provost

          Senior Technical Sales Executive

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            Resolving issues with part name display in eDrawings compared to SOLIDWORKS

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            Resolving issues with part name display in eDrawings compared to SOLIDWORKS

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            It is quite common for information shared with the workshop through eDrawings not to appear exactly as expected. In fact, part names may seem incorrect, incomplete, or simply different from what the engineering team sees in SOLIDWORKS.

            As a result, this is a question we are regularly asked: “Why are part names not the same in eDrawings as in the SOLIDWORKS assembly?”

            So, if you use eDrawings as a viewer for shop floor personnel, this article is for you. Let’s take a few minutes to understand why this happens and more importantly, how to fix it in a sustainable way.

            The Typical Context: eDrawings as a Workshop Support Tool

            In many manufacturing companies, eDrawings is used to:

            • View assemblies without a SOLIDWORKS license;

            • Visualize complete machines on the shop floor;

            • Quickly identify parts to manufacture or assemble;

            • Reduce paper drawings.

            It is an excellent tool as long as the displayed information is clear and consistent.

            However, in some cases, workshop users are faced with:

            • Cryptic file names;

            • Internal references that are not meaningful;

            • Part names different from those used by engineering.

            A Key Point to Understand: eDrawings Does Not Interpret, It Displays

            First of all, it is important thing to clarify: eDrawings does not “guess” anything. It simply displays the information coming from SOLIDWORKS, based on the assembly structure, the properties defined on each part, and the export options used. Therefore, if the display does not meet your expectations, it is almost never an eDrawings bug, but rather a source data or configuration issue.

            The Three Most Common Causes

            In practice, three main causes explain this behavior:

            1. The displayed name is the file name, not the business designation

            By default, eDrawings often displays the part file name (.SLDPRT) instead of:

            • The business designation;

            • The part number;

            • The workshop-oriented description.

            Example: PLT_4587_V3.SLDPRT instead of Conveyor support plate – 10 mm steel

            For the shop floor, the added value is… very limited.

            2. Custom properties are not being leveraged

            Additionally, in SOLIDWORKS, you most likely already have:

            • Description

            • Part Number

            • Internal reference

            • Customer name

            But if these properties are not filled in consistently or eDrawings is not configured to display them, they become useless for the workshop.

             

            3. The eDrawings export process is not standardized

            Finally, an export performed quickly, by different users and without a clear procedure often results in:

            • inconsistent displays;

            • different habits from one project to another.

            As a result, the workshop gradually loses confidence in the tool.

            Recommended Best Practice: Think “Workshop” Directly in SOLIDWORKS

            In reality, the solution is not in eDrawings…it starts in SOLIDWORKS.

            Here is a simple and effective approach:

            Use a workshop-oriented property

            For example:

            • Description

            • or Workshop_Description

            This property should be clear, readable and free of unnecessary CAD jargon.

            Standardize how properties are filled in

            Apply the same logic to all parts:

            • same property name

            • same text convention

            • same language

            Ultimately, this is a small effort on the engineering side…but delivers significant gains on the production side.

             

            Structuring the eDrawings Export for the Workshop

            To ensure consistency, the eDrawings export should:

            • always come from an up-to-date assembly;

            • follow a simple, documented procedure;

            • display useful information, not technical noise.

            This is exactly why a short internal procedure is often an excellent idea.

            eDrawings: An Excellent Tool, When Properly Prepared

            eDrawings is neither a design tool nor a PDM system. It is a technical communication tool.

            In other words, like any communication, quality depends on what is sent, not only on the tool itself.

            As a result, when best practices are in place the workshop gains autonomy, the unnecessary questions decrease, and the interpretation errors are reduced.

            From Confusion to Clarity: Making eDrawings Work for the Workshop

            If part names displayed in eDrawings do not match what you expect, know that you are not alone, it is not inevitable, and it is almost never a bug. More often than not, it is an opportunity to review how information is prepared and transferred to the workshop.

            Very often…a few simple adjustments are enough to turn eDrawings into a true production support tool.

            FAQ

            Why do part names in eDrawings differ from those in SOLIDWORKS?

            eDrawings displays information coming from SOLIDWORKS files, typically the file name or custom properties. If these data are not standardized or workshop-oriented, the display may appear inconsistent.

            Is this an eDrawings bug or limitation?

            No. In most cases, the issue lies in how data is structured upstream in SOLIDWORKS, not in eDrawings itself.

            What is the best practice to display clear part names on the shop floor?

            Use a dedicated, readable SOLIDWORKS property such as Description or Workshop_Description, filled consistently across all parts.

            Is a SOLIDWORKS license required on the shop floor?

            No. eDrawings allows assembly viewing without a SOLIDWORKS license, making it a cost-effective solution for workshop use.

            What is the tangible benefit for the company?

            A clear and standardized eDrawings display helps to:

            • reduce interruptions between engineering and production

            • limit interpretation errors

            • improve overall operational efficiency


            Alain

            Alain Provost

            Senior Technical Sales Executive

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              Guide: Getting Started with AI in SOLIDWORKS

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              Guide: Getting Started with AI in SOLIDWORKS

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              Artificial Intelligence is quickly becoming part of everyday engineering workflows, but if you’re a SOLIDWORKS user, the big question is usually:

              “Where do I even start?”

              The good news is that AI in SOLIDWORKS isn’t something separate you need to learn from scratch. It’s already being integrated into the tools you use every day through the 3DEXPERIENCE platform.

              In this guide, we’ll walk through everything you need to get started, step by step:

              • Required software and prerequisites

              • Activating the 3DEXPERIENCE platform

              • Installing the Design with SOLIDWORKS connector

              • Accessing AI tools like the new AI Labs tab

              No fluff, just what you need to get up and running.

              Step 1: Understand What “AI in SOLIDWORKS” Actually Means

              Before jumping into setup, it’s important to clarify something:

              AI in SOLIDWORKS isn’t a single feature. It’s a set of capabilities delivered through the 3DEXPERIENCE platform.

              Today, that includes things like:

              • Design assistance and recommendations

              • Automation of repetitive tasks

              • Data-driven insights

              • Early access tools in AI Labs

              In other words, AI is layered into your workflow, not replacing it.

              Step 2: Confirm Your Prerequisites

              Before you can access any AI-driven tools, you’ll need a few key components in place.

              Required Software

              • SOLIDWORKS 2026 (or newer)

              • Active subscription (required for cloud services integration)

              Platform Access

              • A 3DEXPERIENCE platform account

              • Assigned roles (including Collaborative Designer for SOLIDWORKS)

              System Requirements

              • Stable internet connection

              • Admin rights for installation

              • Browser access to the platform

              If you’re missing any of these, that’s your starting point.

              Step 3: Activate the 3DEXPERIENCE Platform

              AI functionality depends on your connection to the 3DEXPERIENCE platform.

              How to Activate:

              • Check your welcome email from Dassault Systèmes
              • Click the activation link
              • Set your password and log in
              • Access your platform dashboard

              Once inside, you should see your roles and available apps.

              Still confused? Follow our Getting Started guide:
              Getting Started with the 3DEXPERIENCE Platform

              Step 4: Install the 3DEXPERIENCE Launcher

              Before installing any apps, you’ll need the 3DEXPERIENCE Launcher.

              Steps:

              • Log into your 3DEXPERIENCE platform
              • Navigate to the Compass (top-left menu)
              • Scroll down to My Apps and locate Design with SOLIDWORKS.
              • Select the app to begin the installation.
              • Click Install Launcher when prompted
              • Run the installer

              This tool acts as the bridge between your browser and desktop applications.

              Step 5: Install “Design with SOLIDWORKS”

              This is the most important step.

              The Design with SOLIDWORKS connector is what links your desktop SOLIDWORKS environment to the platform, and enables AI-driven features.

              Installation Steps:

              • In the platform, search for Design with SOLIDWORKS
              • Click Install
              • Accept default settings (recommended)
              • Complete installation
              • Restart your machine if prompted

              Once installed, your environment is officially “connected.”

              Having trouble? Check out our installation guide:
              Connect SOLIDWORKS Desktop to the 3DEXPERIENCE Platform

              Step 6: Launch SOLIDWORKS from the Platform

              This step is often missed, however, it is absolutely critical.

              First Launch:

              • Go to the platform
              • Click Open on Design with SOLIDWORKS
              • Launch SOLIDWORKS from the browser

              Why this matters:

              This ensures:

              • Your session is authenticated
              • The connector is active
              • Cloud services are initialized

              If you launch SOLIDWORKS directly from your desktop first, you may not be connected properly.

              Step 7: Verify the 3DEXPERIENCE Add-in

              Once SOLIDWORKS opens, confirm everything is working.

              Check:

              • A 3DEXPERIENCE tab appears in the task pane
              • Add-in is enabled under:
                Tools > Add-ins

              If it’s not active:

              • Enable it manually
              • Restart SOLIDWORKS if needed

              This confirms your system is fully connected.

              Step 8: Access the AI Labs Tab

              Now we get to the interesting part.

              With everything configured, you should have access to AI Labs, where new AI-driven tools are introduced.

              Where to Find It:

              • Inside SOLIDWORKS (Task Pane)
              • Look for AI Labs tab

              What You’ll Find:

              • Experimental AI features
              • Early access tools
              • Workflow enhancements powered by AI

              These features evolve quickly, so expect changes over time.

              Step 9: Start Using AI Features (Practical Examples)

              Once inside AI Labs or connected tools, start small.

              Good First Use Cases:

              • Automating repetitive design steps
              • Getting design suggestions
              • Exploring data-driven insights

              What Not to Expect:

              • Fully automated design generation
              • “One-click engineering”

              AI is there to assist, not replace your expertise.

              Step 10: Best Practices for Getting Started

              This is where most teams succeed or struggle.

              ✔ Start Small

              Don’t try to overhaul your entire workflow.

              ✔ Focus on Real Problems

              Look for:

              • Repetitive tasks
              • Bottlenecks
              • Manual processes

              ✔ Validate Everything

              AI suggestions still require engineering judgment.

              ✔ Train Your Team Gradually

              Adoption works best when it’s incremental.

              Final Thoughts: Where AI in SOLIDWORKS Is Headed

              AI in SOLIDWORKS is evolving, but the direction is clear:

              • More automation of low-value tasks
              • Better decision support
              • Deeper integration with simulation and data

              And importantly:

              SOLIDWORKS isn’t being replaced, it’s being enhanced.

              For most teams, the real opportunity isn’t jumping ahead, it’s simply getting started.

              For more information on AI in SOLIDWORKS, reach out to us through our website:
              SOLIDWORKS AI: Transform Your Design with Artificial Intelligence


              Michael Habrich

              3DEXPERIENCE Specialist

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              Whether you’re ready to get started or just have a few more questions, you can contact us toll-free:

                Connecting SOLIDWORKS Desktop to the 3DEXPERIENCE Platform

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                Connecting SOLIDWORKS Desktop to the 3DEXPERIENCE Platform

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                The 3DEXPERIENCE platform includes a wide range of powerful, web-based apps, but many teams prefer to continue designing in the familiar SOLIDWORKS desktop environment. The good news? You don’t have to choose one or the other.

                By combining SOLIDWORKS desktop with the Design with SOLIDWORKS connector, you can keep your existing workflows and interface while taking full advantage of cloud-based file storage, sharing, and collaboration.

                In this article, we’ll walk through:

                • Installing the Design with SOLIDWORKS connector

                • Launching SOLIDWORKS with the 3DEXPERIENCE connection enabled

                • Saving files directly to the platform

                • Managing your local cache for best performance

                Installing Design with SOLIDWORKS

                First, once your 3DEXPERIENCE tenant is activated, or you’ve been invited to an existing one , linking SOLIDWORKS desktop to the platform is quick and straightforward.

                • In the 3DEXPERIENCE interface, click the Compass icon in the upper-left corner.

                • Scroll down to My Apps and locate Design with SOLIDWORKS.

                • Select the app to begin the installation.

                Installing Design with SOLIDWORKS

                During installation, you’ll be prompted to:

                • Install all granted roles, or

                • Install only the roles required for the Design with SOLIDWORKS connector

                Installing Design with SOLIDWORKS

                The installer will then allow you to choose:

                • The installation directory

                • The location of your 3DEXPERIENCE cache

                By default, the cache is stored in C:\3DEXPERIENCE. Since the cache is managed directly from within SOLIDWORKS, you typically won’t need to access this folder manually.

                The cache is stored in C:\3DEXPERIENCE

                Once installation is complete, the connector is added to your system.

                Enabling the 3DEXPERIENCE Add-In in SOLIDWORKS

                Before using the connector, take a moment to confirm the 3DEXPERIENCE add-in is enabled in SOLIDWORKS.

                • Launch SOLIDWORKS.

                • Go to Settings > Add-Ins.

                • Verify that the 3DEXPERIENCE add-in is installed and checked.

                Enabling the 3DEXPERIENCE Add-In in SOLIDWORKS

                This ensures SOLIDWORKS can communicate properly with the platform.

                Launching SOLIDWORKS with the Connector

                One important workflow change to be aware of is how you launch SOLIDWORKS.

                • Launching SOLIDWORKS from a desktop shortcut or system search opens the standard desktop version without the 3DEXPERIENCE connection.

                • To use the connector, launch Design with SOLIDWORKS instead.

                This starts SOLIDWORKS with full 3DEXPERIENCE functionality enabled.

                You can also:

                • Use the dropdown next to Design with SOLIDWORKS to check for updates or uninstall

                • Create a dedicated desktop shortcut for Design with SOLIDWORKS, allowing you to access cloud functionality without opening a web browser

                Launching SOLIDWORKS with the Connector

                Saving Files to the 3DEXPERIENCE Platform

                Once connected, saving files to the cloud is seamless.

                You can:

                • Use Save to 3DEXPERIENCE from the File menu (alongside Save and Save As), or

                • Use the 3DEXPERIENCE Task Pane, added by the add-in

                The task pane lets you:

                • Browse your tenant

                • Search for existing data

                • Right-click and save files directly to the platform

                And if needed, you can still save files locally, the connector doesn’t force you into a cloud-only workflow.

                Saving Files to the 3DEXPERIENCE Platform

                Managing the 3DEXPERIENCE Cache

                When you open or edit files stored on the platform, they’re downloaded locally to your 3DEXPERIENCE cache. Keeping this cache clean can significantly improve performance.

                The 3DEXPERIENCE add-in makes cache management easy:

                • Delete individual cached files

                • Use the cleanup tool to remove files older than a specified date

                The cleanup utility is smart. It automatically skips:

                • Files referenced by assemblies

                • Files not yet saved to the platform

                • Files that are currently locked

                This helps you clear space without risking your data.

                Saving Files to the 3DEXPERIENCE Platform

                Final Thoughts

                The Design with SOLIDWORKS connector bridges the gap between SOLIDWORKS desktop and the 3DEXPERIENCE platform, giving you the best of both worlds. You get cloud-based collaboration and data management without changing how you design.

                If you need help installing the connector, optimizing your workflow, or rolling this out to your team, your Solidxperts team is here to help.

                Looking to learn more?

                • Explore additional articles and tutorials

                • Connect with other users and experts

                • Or reach out to us! We’re always happy to help you get the most out of your tools


                Michael Habrich

                3DEXPERIENCE Specialist

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                  7 Myths About AI: Demystifying Bias and Technological Limits

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                  7 Myths About AI: Demystifying Bias and Technological Limits

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                  Every wave of innovation in artificial intelligence (AI) brings real technological progress, along with a dramatic rise in hype. With every breakthrough, new narratives emerge: AI is portrayed as “magical,” endowed with its own will, on the verge of becoming superhuman, or conversely as something completely uncontrollable by law.

                  As a result, this fog of myths makes AI opaque to the public, complicates decision-making for organizations, and distracts attention from the real technical and societal challenges.

                  In this article, we aim to clarify two key questions:

                  • What are the main myths currently surrounding AI?

                  • And what technical, physical, and social realities help dismantle them?

                  The Major Myths Shaping Our View of AI

                  Several myths structure today’s collective imagination about artificial intelligence.

                  “AI has agency.”
                  The idea that AI systems act on their own initiative, with intentions, goals, or desires.

                  “Superintelligence is imminent.”
                  The belief that we are only a few years, or even months, away from a general intelligence far surpassing human capabilities.

                  “AI can be objective or impartial.”
                  The assumption that algorithms are inherently neutral because they rely on computation.

                  “AI has a clear definition.”
                  As if AI referred to a single, clearly defined technology, when in reality no universal definition exists.

                  “Ethical guidelines are enough to protect us.”
                  The perception that voluntary ethical charters are sufficient safeguards against harmful AI uses.

                  “AI cannot be regulated.”
                  The claim that technological innovation moves too fast for legal systems to keep up.

                  “AI can solve any problem.”
                  The idea that AI is a universal solution applicable to any technical, economic, or social challenge.

                  In reality, these myths stem from a mixture of marketing, science fiction, and technical misunderstanding. To move beyond them, we need to return to what AI actually is today.

                  1. Agency and Consciousness: AI as a “Stochastic Parrot”

                  One of the most common misconceptions is attributing intention to AI. We often talk about what AI “wants,” “decides,” or “thinks.” Yet modern systems, especially large language models (LLMs), function much more simply.

                  Models That Predict, Not Understand

                  An LLM does not interpret your sentences in the human sense. Technically, it:

                  • receives a sequence of tokens (pieces of words) as input

                  • computes a probability distribution over the next token using a trained neural network

                  • selects or samples the next token according to this distribution

                  • repeats the process until a complete response is produced

                  This mechanism relies on massive statistical correlations learned during training. At no point does the system possess:

                  • semantic understanding of concepts

                  • an internal model of the world comparable to a human’s

                  • independent intentions or goals

                  In other words, what researchers sometimes call a “stochastic parrot”: a machine that reproduces learned language structures in sophisticated probabilistic combinations.

                  Anthropomorphism as a Persistent Bias

                  If these systems appear to “think,” it is largely because humans naturally anthropomorphize systems that display seemingly intelligent behavior. This cognitive bias is central to many misunderstandings about AI today.

                  2. Superintelligence and the Resource Wall

                  Another dominant narrative suggests that we are on the verge of general superintelligence, held back only by corporate caution. However, the actual infrastructure behind AI tells a different story.

                  The Data Wall: A Finite Resource

                  Today’s large models rely on enormous volumes of high-quality human-generated data: text, conversations, code, and multimedia content. But this resource is not infinite.

                  Estimates suggest that high-quality training data suitable for ever-larger models could be largely exhausted between 2026 and 2032. Beyond that point:

                  • existing datasets would be reused repeatedly, yielding limited improvements

                  • or synthetic data would be used, introducing new risks and feedback loops

                  Physical Constraints and Diminishing Returns

                  The idea of unlimited growth in model power faces several practical limits.

                  Energy and cooling constraints
                  The computing density required for training and deploying the largest models pushes data centers toward limits in:

                  • electrical grid capacity

                  • cooling infrastructure needed to dissipate heat

                  Hardware limits
                  GPUs and other accelerators are approaching physical limits in terms of performance per watt and cost efficiency.

                  Diminishing returns
                  Scaling models by increasing parameters, data, or compute still improves performance, but each additional gain becomes smaller relative to the resources invested.

                  These “resource walls” do not prevent progress, but they challenge the idea of a straightforward path toward limitless superintelligence.

                  3. Objectivity and Impartiality: AI as a Mirror of Human Bias

                  AI is often presented as a way to eliminate human bias. In reality, AI systems frequently inherit and sometimes amplify existing inequalities.

                  Data Bias: Who Is Represented?

                  Models can only generalize effectively if training data represent a sufficiently diverse set of situations and populations.

                  When datasets are imbalanced, performance degrades unevenly. Studies have shown, for instance, that some facial recognition systems exhibit error rates up to 35% higher for darker-skinned women than for white men.

                  This is not an isolated bug. It reflects underlying representation biases in the data.

                  Design Bias: Optimization Choices Matter

                  Even with balanced datasets, models reflect the priorities of their designers:

                  • How is overall accuracy balanced against fairness between groups?

                  • Which metrics are optimized during training and deployment?

                  • What trade-offs are accepted between false positives and false negatives?

                  These decisions directly shape who benefits from an AI system and who may be harmed. Claims of algorithmic objectivity often overlook these design choices.

                  4. The Plural Architecture of AI

                  Contrary to popular belief, “artificial intelligence” does not describe a single unified technology. Instead, it is an umbrella term covering a broad and heterogeneous set of methods, theories, and applications.

                  A Hierarchy of Often-Confused Concepts

                  Many people use AI, Machine Learning, and Deep Learning interchangeably, although they represent different levels of abstraction.

                  Artificial Intelligence (AI)
                  The broader field of computer science focused on creating systems capable of performing tasks that require human-like cognitive abilities.

                  Machine Learning (ML)
                  A subset of AI in which systems learn patterns from data rather than relying solely on explicit programming.

                  Deep Learning (DL)
                  A specialized ML approach using multi-layer neural networks to process complex data such as images, speech, or language.

                  Divergent Definitions

                  The meaning of AI changes depending on perspective.

                  • Scientific definition: a research discipline exploring computational models of cognition.

                  • Technological definition: systems capable of perceiving their environment and taking actions accordingly.

                  • Popular definition: a largely anthropomorphic vision attributing awareness or autonomy to machines.

                  A Fragmented Ecosystem

                  AI is not monolithic. It includes multiple research traditions and technical approaches.

                  Two historical families illustrate this diversity:

                  Symbolic AI
                  Systems based on logical rules and expert knowledge.

                  Connectionist AI
                  Statistical approaches based on large datasets and neural networks, including modern language models.

                  Narrow AI vs General AI

                  Today’s systems belong entirely to narrow AI, designed to perform specific tasks such as:

                  • playing chess

                  • recognizing objects in images

                  • detecting fraud

                  • generating text

                  Artificial General Intelligence (AGI), capable of learning any intellectual task a human can perform, remains a speculative concept.

                  5. Ethics, Marketing, and the Need for Regulation

                  In response to AI risks, many organizations have adopted ethical charters and voluntary guidelines. While useful, these tools have clear limitations.

                  Ethical Marketing

                  Without enforcement mechanisms, many ethical charters function more as reputation tools:

                  • they reassure stakeholders

                  • they improve brand image

                  • but they rarely prevent high-risk systems from being deployed

                  Toward Enforceable Regulation: The EU AI Act

                  Contrary to the myth that AI cannot be governed, regulatory frameworks are emerging.

                  The European Union’s AI Act proposes a risk-based approach:

                  • Unacceptable risk systems are banned

                  • High-risk systems must comply with strict requirements including transparency, traceability, documentation, conformity assessments, and human oversight

                  • Minimal risk systems face limited regulation

                  The goal is not to slow innovation, but to ensure that AI systems remain accountable within existing legal frameworks.

                  6. AI Is Not a Magic Wand

                  Perhaps the most persistent myth is that AI can solve any problem.

                  In reality, successful AI systems are:

                  • specialized, designed for specific tasks such as image recognition, text summarization, fraud detection, or code generation

                  • limited in common sense, often failing when faced with situations outside their training distribution

                  • highly context-dependent, relying on data quality, system integration, and human oversight

                  The same model may perform extremely well in a well-defined environment yet fail dramatically when conditions change or when real-world usage diverges from intended scenarios.

                  AI as a Component, Not a Strategy

                  For organizations, AI should be viewed as:

                  • a technical component within a larger system architecture

                  • integrated into a broader strategy involving governance, metrics, risk management, and human supervision

                  The wrong question is:

                  “How can we add AI everywhere?”

                  The better question is:

                  “On which well-defined problems does AI provide a real advantage compared to existing solutions?”

                  Moving Beyond the Myths

                  Today’s AI is neither a conscious entity, nor an imminent superintelligence, nor a universal solution.

                  It is a set of powerful techniques deeply grounded in real-world constraints. These systems are limited by physical infrastructure such as energy, cooling, and hardware, as well as by the availability of data and computational resources. They are also shaped by the social structures and human biases embedded in the data and objectives guiding their development.

                  By dismantling the myths surrounding AI, autonomous agency, imminent superintelligence, perfect objectivity, legal ungovernability, or universal applicability, we can ask better technical questions, design safer systems, and build more effective regulatory frameworks.

                  Ultimately, understanding these realities allows us to treat AI for what it truly is: a powerful but specialized tool that must be used with rigor, transparency, and human oversight.

                  If you have questions about AI and its practical applications, our experts are here to help. Contact us to start the conversation.


                  Benoit Bilodeau

                  Senior Solutions Architect

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                  Whether you’re ready to get started or just have a few more questions, you can contact us toll-free:

                    SWOOD and Material Management: From Design to Wood Manufacturing

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                    SWOOD and Material Management: From Design to Wood Manufacturing

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                    Material is More Than Just a Visual Appearance

                    In the furniture, cabinetry, and commercial millwork industries, material selection plays a critical role. It impacts not only product aesthetics, but also manufacturability, cost control, quality, and production repeatability. Yet, in many organizations, material management is still treated as a secondary concern, often limited to a visual texture or a late-stage production note.

                    As a result, this approach frequently leads to well-known issues. Designers and production teams may face inconsistencies between design and the shop floor, incorrect panel selection, edge banding errors, material waste, and costly rework. In addition, standardizing internal processes becomes much more difficult.

                    At a time when companies are striving to improve operational efficiency and production reliability, these issues can quickly turn into costly bottlenecks.

                    This is where the combination of SOLIDWORKS and SWOOD makes a real difference. By integrating intelligent material management directly into the design phase, SWOOD transforms materials into structured, manufacturing-ready data. As a result, this information remains consistent throughout the entire digital workflow.

                    The Limitations of Material Management in SOLIDWORKS

                    SOLIDWORKS is a powerful and flexible CAD platform, widely recognized for its robustness and parametric capabilities. In addition, it offers advanced material handling for mechanical design, including physical properties, mass calculations, and rendering. However, when applied to wood-based design, certain limitations quickly emerge.

                    In fact, native SOLIDWORKS materials are primarily intended for mechanical applications. As a result, they do not fully address the realities of wood manufacturing, such as:

                    • engineered wood panels,

                    • commercial panel thicknesses,

                    • wood grain direction,

                    • supplier-specific decors,

                    • edge banding compatibility,

                    • or CNC manufacturing constraints.

                    As a result, designers often rely on generic materials and manual adjustments. This information remains disconnected from manufacturing processes, forcing production teams to reinterpret design intent. The lack of continuity increases error risks and severely limits automation.

                    Why Material Management Is Critical in Wood Design?

                    In wood design, materials are never neutral. A panel is not simply a thickness and a color. Instead, it represents a supplier, a finish, compatible edge banding, machining rules, and cost implications.

                    Without proper material definition, several issues can arise. For example, poor material management can lead to:

                    • incorrect panel usage in production,

                    • edge banding mismatches,

                    • nesting inefficiencies,

                    • inaccurate material cost estimates,

                    • and inconsistencies across similar projects.

                    On the other hand, structured material management allows companies to:

                    • ensure design-to-production consistency,

                    • reduce manual data entry,

                    • improve communication between departments,

                    • and secure manufacturing outcomes early in the design process.

                    In this context, materials become a strategic data asset, just as critical as dimensions or tolerances.

                    How SWOOD Structures Material Management?

                    Material Libraries Designed for the Wood Industry

                    SWOOD introduces material libraries specifically developed for cabinetry, furniture, and millwork professionals. Unlike generic CAD materials, these libraries are designed to reflect real manufacturing requirements. As a result, SWOOD materials include production-relevant parameters such as:

                    • actual panel thickness,

                    • material type (MDF, melamine, plywood, solid wood, etc.),

                    • grain direction,

                    • tolerances,

                    • and attributes required for bills of materials and cut lists.

                    These libraries can be standardized company-wide, ensuring consistent practices across all projects and designers.

                    Direct Link Between Materials and CNC Manufacturing

                    One of SWOOD’s key strengths is the direct connection between materials and manufacturing processes. Because of this, materials are no longer used only for visualization. Instead, they actively drive CNC machining behavior.

                    Based on the selected material, SWOOD can:

                    • adapt machining strategies,

                    • select appropriate tools,

                    • control cutting depths,

                    • and automatically prepare data for production.

                    This significantly reduces manual adjustments on the shop floor and improves manufacturing reliability, even for highly customized projects.

                              

                    Edge Banding and Decor Management

                    Edge banding is a critical aspect of wood manufacturing. SWOOD enables intelligent associations between panels and compatible edge banding materials.

                    Decors are not used solely for visualization. They are also embedded into:

                    • bills of materials,

                    • cut lists,

                    • nesting data,

                    • and shop floor documentation.

                    By automating these relationships, SWOOD minimizes human error and ensures consistent data from design through production.

                    From Design to Manufacturing: A Controlled Digital Continuity

                    SWOOD is built around the concept of digital continuity. Data defined during design is the same data used for manufacturing, without re-entry or reinterpretation.

                    A typical workflow includes:

                    1. Designing furniture or millwork in SOLIDWORKS with SWOOD Design.

                    2. Applying structured, manufacturing-ready materials.

                    3. Transferring data directly to SWOOD CAM and SWOOD Nesting.

                    4. CNC production driven by consistent and reliable information.

                    This approach improves traceability, reduces lead times, and increases overall production confidence.

                    The Impact on Costs and Industrial Performance

                    Effective material management directly impacts business performance. By integrating materials early in the design phase, companies can:

                    • improve material cost estimation accuracy,

                    • reduce waste and scrap,

                    • optimize panel nesting,

                    • standardize internal workflows,

                    • and accelerate onboarding of new employees.

                    These benefits are especially valuable for growing organizations that need scalable and repeatable processes.

                    Which Companies Benefit Most from SWOOD Material Management?

                    SWOOD material management is particularly valuable for:

                    • furniture manufacturers,

                    • commercial millwork companies,

                    • industrial cabinet makers,

                    • CNC woodworking shops,

                    • and organizations seeking to structure or automate their design-to-production workflows.

                    Regardless of company size, this approach increases reliability, productivity, and competitiveness.

                    Why SWOOD Is the Best Solution for Wood Design in SOLIDWORKS

                    SWOOD does not replace SOLIDWORKS, it enhances it. It adds a critical industry-specific layer tailored to wood manufacturing requirements. By combining SOLIDWORKS’ parametric power with SWOOD’s manufacturing intelligence, companies gain a coherent, scalable, and production-oriented environment.

                    This integration unlocks the full potential of the digital manufacturing chain, from design through CNC production.

                    Material as a Core Element of the Digital Wood Workflow

                    In modern wood manufacturing, materials can no longer be treated as simple visual properties. Instead, they must be managed as essential design and manufacturing data that supports the entire production process.

                    When material management is structured properly, companies gain much better control over their operations. With SWOOD, wood manufacturers can reduce errors, better control material costs, and improve overall production reliability.

                    Ultimately, integrating materials early in the design phase helps create a more consistent and efficient workflow from design to manufacturing.

                    Looking to improve your material management and secure your digital workflow from design to production? Solidxperts helps wood manufacturing companies implement SWOOD, train their teams, and optimize their design-to-production processes.

                    FAQ

                    What are the financial benefits of materials management with SWOOD?

                    Materials management with SWOOD reduces manufacturing errors, rework, and material waste. By standardizing materials from the design stage, companies improve the accuracy of cost estimates, optimize nesting, and reduce scrap, generating a measurable return on investment from the very first projects.

                    How does SWOOD contribute to reducing production errors?

                    SWOOD eliminates information gaps between the design office and the shop floor. Materials defined during the design phase are used directly in CNC manufacturing, without re-entry. This digital continuity significantly reduces errors related to incorrect panels, incompatible edges, or incorrect machining parameters.

                    Does SWOOD improve the productivity of the design office?

                    Yes. By using standardized material libraries, designers spend less time checking or correcting material information. Projects are faster to design, more consistent, and easier to reuse, improving overall engineering productivity.

                    What is the impact of SWOOD on time to market?

                    By reducing manual approvals and last-minute adjustments, SWOOD accelerates the transition from design to manufacturing. With reliable data from the design stage, time to market is shortened and bottlenecks between departments are reduced.

                    Does managing materials with SWOOD facilitate company growth?

                    Yes. SWOOD helps structure internal processes, which is essential for supporting growth. Standardized practices, reduced reliance on key experts, and faster onboarding of new employees allow the company to grow without a proportional increase in operational risks.

                    How can the ROI be concretely measured after implementing SWOOD?

                    ROI can be measured through several indicators: reduced scrap, shorter design time, fewer production errors, improved panel utilization, and shorter delivery times. These indicators are easily observable before and after implementation.

                    Is SWOOD profitable for a wood industry SME?

                    SWOOD is particularly well-suited to SMEs. The gains from reduced errors, optimized material usage, and improved productivity quickly offset the initial investment. Many SMEs see a return on investment within a few months, especially when producing diverse or custom projects.

                    Does SWOOD help secure internal knowledge and standards?

                    Yes. SWOOD’s material libraries and design rules allow for the formalization of company standards. This reduces reliance on individual knowledge and safeguards expertise, even in the event of staff turnover.


                    Alain

                    Alain Provost

                    Senior Technical Sales Executive

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