Guide: Getting Started with AI in SOLIDWORKS

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Guide: Getting Started with AI in SOLIDWORKS in 2026

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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 Virtual Companions

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

AI Evolution in SOLIDWORKS

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 Virtual Companions Tab

Now we get to the interesting part.

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

Where to Find It:

  • Inside SOLIDWORKS (Task Pane)
  • Look for Virtual Companions tab

Virtual Companions 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 Virtual Companions, click the potion icon the top right to explore SOLIDWORKS AI competencies:

Virtual Companions

Good First Use Cases:

Click the different categories for examples of prompts you can use to get started.

AI Companion First Case

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

          Artificial Intelligence in Engineering: Automation Without Losing the Human Touch

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          Artificial Intelligence in Engineering: Automation Without Losing the Human Touch

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          Artificial intelligence (AI) is playing an increasingly important role in engineering processes, particularly when it comes to automating repetitive tasks and accelerating the production of technical documentation. However, its role remains fundamentally complementary to that of engineers. Creativity, domain expertise, and decision-making responsibility remain human.

          In this article, we explore:

          • what AI concretely brings to engineering

          • which tasks remain (and will remain) human

          • how to organize an effective human–machine collaboration

          • and what this means for the engineering profession

          1. What AI concretely brings to engineering

          1.1 Automating repetitive, low-value tasks

          The daily work of engineering teams is filled with essential but repetitive tasks that consume a great deal of time without fully leveraging engineers’ expertise. This is precisely where AI excels.

          A typical example is generating technical drawings from 3D models.

          Traditionally, producing technical drawings involves:

          • manually creating the different views (front, section, detail views)

          • applying dimensioning and tolerancing standards

          • reusing elements from previous projects, often manually

          • performing successive checks for consistency and compliance

          With AI, a large portion of this work can be:

          • automated: generating technical drawings directly from 3D designs

          • contextualized: taking into account company history, internal standards, and previously validated models

          The result: fewer repetitive clicks and more time for analysis and improvement.

          1.2 Measurable efficiency gains

          The operational impact is far from marginal.

          Where dozens of people were previously needed to produce, adjust, and verify detailed drawings, organizations can now concentrate human work within a smaller team of reviewers responsible for:

          • correcting the remaining inconsistencies

          • validating compliance

          • managing special cases not covered by the models

          AI handles the repetitive heavy lifting. Humans focus on quality, reliability, and exception management.

          2. Tasks that remain (and will remain) human

          Despite these gains, certain activities remain difficult to automate and may remain so in the short and medium term.

          2.1 Creative design and early project phases

          The early stages of a project, when the architecture of a product and the major technical choices are defined, rely on:

          • creativity

          • accumulated domain expertise

          • the ability to integrate sometimes ambiguous constraints (real-world usage, environment, maintenance, ergonomics)

          • complex decision-making that affects overall product performance

          These activities require systemic understanding, multi-criteria trade-offs, and a form of intuition that current AI models cannot replicate.

          2.2 Safety, compliance, and responsibility

          A clear example is the design of powerful machinery.

          Engineers must:

          • integrate safety factors to protect users

          • sometimes introduce additional margins based on experience or real-world conditions that are difficult to simulate

          These decisions directly affect safety, regulatory compliance, and legal responsibility.

          Today, these types of decisions cannot be delegated to AI.
          Decision-making responsibility remains with humans, not algorithms.

          3. Toward intelligent human–machine collaboration

          The key question is therefore not whether AI will replace engineers, but how to organize an effective collaboration between the two.

          3.1 AI as a copilot during design

          During the design process, AI can act as a copilot or technical assistant. For example, it can:

          • propose lighter materials that still meet strength requirements

          • suggest geometric variations to reduce weight or improve rigidity

          • quickly analyze the impact of small design changes on overall performance

          In practice, engineers can ask AI questions such as:

          • “Which materials meet these strength and weight constraints?”

          • “What geometric alternatives could reduce the mass by 10 percent?”

          However, final validation, trade-off decisions, and system integration remain the responsibility of the engineer.

          3.2 AI as an analyst for standardized tasks

          For more standardized analytical tasks, AI becomes a particularly useful engineering assistant. It can support:

          • the processing and structuring of large volumes of data

          • the automatic generation of variants for comparative studies

          • consistency checks across large sets of technical documentation

          This allows teams to explore more possibilities in less time, without removing the engineer from the decision-making process.

          4. Should engineers fear being replaced by AI?

          The fear of being replaced by machines is real and understandable, especially in technical professions.

          4.1 Vulnerable jobs vs resilient jobs

          A job is more exposed to automation when its tasks are:

          • repetitive

          • highly standardized

          • not very creative

          • associated with limited decision-making

          In contrast, a job is more resilient when it involves:

          • significant creativity

          • a global understanding of complex systems

          • multi-criteria trade-offs (cost, performance, risk, environmental impact)

          • strong responsibility for safety, compliance, or performance

          In engineering, activities such as:

          • defining a product’s overall architecture

          • breakthrough innovation

          • high-impact technical decisions

          • field responsibility

          remain firmly within the human domain.

          4.2 A change in role rather than disappearance

          Consider the example of technical documentation.

          Yes, AI can generate documents based on validated models or historical data.

          No, it does not replace engineers when it comes to:

          • critical decision-making

          • technical trade-offs

          • creative innovation

          What changes most is how time is allocated:

          • less manual and repetitive production work

          • more design, analysis, validation, and innovation

          Toward augmented engineering, not automated engineering

          Artificial intelligence brings real value to engineering by:

          • automating repetitive, low-value tasks

          • accelerating the generation of drawings and technical documentation

          • assisting engineers in exploring design alternatives and performing analysis

          However, creativity, domain expertise, and responsibility remain central to the engineer’s role.

          The goal is not to replace humans, but to build intelligent collaboration:

          • letting AI handle what it does best (speed, repetition, scale)

          • preserving what defines engineering expertise: inventing, evaluating trade-offs, and taking responsibility for decisions

          The future of engineering will not be “human or AI,” but clearly human + AI: augmented engineering that is more efficient, safer, and more focused on innovation.


          Benoit Bilodeau

          Senior Solutions Architect

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            How to Define Bonded Interactions in SOLIDWORKS Simulation: A Practical Case Study

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            How to Define Bonded Interactions in SOLIDWORKS Simulation: A Practical Case Study

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            Are you wondering which interaction type should be used in SOLIDWORKS Simulation to represent a weld or to attach two bodies so they do not separate during the analysis?

            Think about a bracket supporting critical components of a product. What must be done to ensure that the simulation accurately represents the real behavior before running the analysis?

            After reading this blog, you will be familiar with the key steps required to properly define bonded interactions in SOLIDWORKS Simulation. 

            Representation of the bonded interaction

            In SOLIDWORKS Simulation, a bonded interaction is used to connect two or more bodies so that no relative motion is allowed at their interface. A typical example is welding a bracket to another component to reinforce a structure and reduce stress in critical areas.

            A bonded interaction is equivalent to merging bodies while still allowing each part to retain its own material properties. Once defined, the connected bodies are assumed to never separate during the analysis. This represents an idealized, perfectly rigid weld. While such a condition does not exist in reality, it is often a reasonable and efficient assumption when a near-perfect weld behavior is expected.

            A bonded interaction should not be used to represent a contact condition (formerly called No Penetration) or any situation where sliding between components is expected.

            In some cases, however, it may be acceptable to use a bonded interaction instead of defining multiple contact conditions in order to simplify the analysis. An example is a threaded rod, where detailed local behavior is not required and where the objective is to capture the global structural response rather than local stresses.

            Mesh refinement plays a key role in obtaining accurate results near bonded interaction regions. Adjusting the global mesh parameters or applying local mesh controls can significantly improve mesh consistency at the interface and help ensure reliable and meaningful results.

            Modeling Assumptions: Using Bonded Interactions in a Welded Structure

            We are going to consider the following case study to illustrate the bonded interaction application. See the image below:

            Jib crane case study highlighting potential bonded interaction locations
            Jib crane case study highlighting potential bonded interaction locations

            In this jib crane case study, the gusset parts are welded to the column and base plate to increase the overall resistance of the local area. Because of the nature of the problem, we make the assumption that the parts are tied together and that there is no relative motion between them. Therefore, we can apply a bonded interaction at this location to represent multiple welding interactions.

            Please note that it is not necessary to model the weld as a separate part or body in SOLIDWORKS. This simplifies both the model and the analyst’s work while requiring only minimal additional information.

            As with any modeling assumption, the use of bonded interactions should always be aligned with the objectives of the analysis and the level of accuracy required.

            Global vs Local Bonded Interactions: Setup and Best Practices

            Here we are, the most sought after section of this blog on how to define the bonded interaction. There are several ways to define bonded interactions in SOLIDWORKS Simulation. The good news is that the default option when creating a stress analysis with SOLIDWORKS Simulation is set to apply a bonded interaction at a global level. This means that for coincident solid bodies, no additional interaction definition is required as long as the global interaction type is set to Bonded. The global bonded interaction can be found in the Simulation Tree in the Connections folder, under Component Interactions. Additional options can be set to take into account a gap between the bodies. The following image shows a case where a bonded interaction already defined by default could already be sufficient, meaning that there is no additional required step:

             Alternative jib crane design where the gussets fit into slotted holes
            Alternative jib crane design where the gussets fit into slotted holes

            In some specific cases, a bonded interaction must be defined at a local level which requires a definition in the software. It could be the case of parts with different mesh types or geometry inconsistencies. Let’s consider the case study where there is a small gap between the gusset and the column where a bonded interaction is needed to represent a welding.

            To define a local bonded interaction:

            1. In the Simulation Tree, right-click Connections and select Local Interaction.

            1. In Type, choose Bonded.

            1. In the blue selection box, select the first entity (ideally the smaller one).

            1. In the pink selection box, select the second entity (ideally the larger one).

            1. Multiple entities can be selected if required.

            1. If necessary, define additional options such as the gap tolerance.

            Local bonded interaction definition
            Local bonded interaction definition

            Interpreting Results When Using Bonded Interactions

            When the calculations complete and that we are at the step of validating the results, it is very important to understand how they should be interpreted. Adding unnecessary bonded interactions tends to artificially increase the stiffness of the structure. This can make the model appear stronger than it actually is, resulting in a non-conservative analysis. Therefore, it is important to keep that in mind and make sure that the analysis represents the real case study appropriately. An animation of the results is an excellent way to determine whether or not the structure behaves as it should be. Expect stress concentrations near edges with bonded interactions and pay attention to stress singularities. If necessary, plot the reaction forces and compare them with the applied loads. If the results don’t make sense, it is important to consider reviewing the analysis setup and rerunning the analysis.

            Key Takeaways on Bonded Interactions in SOLIDWORKS Simulation

            In this blog, we explored the application of bonded interactions to better understand their meaning and areas of use.

            Through the lifting jib crane case study, we illustrated the creation of both global and local bonded interactions. In Finite Element Analysis (FEA), the quality of results depends primarily on the relevance of your modeling assumptions and choices.

            Beyond interactions, there are other features that must be used properly to produce reliable simulations tailored to your objectives. If you wish to deepen your knowledge of SOLIDWORKS Simulation, several resources are available to support your progress.

            You can visit our website to read our other technical blogs and learn more: https://solidxperts.com/en/blog/


            Chung Ping Lu, eng.

            Chung Ping Lu, eng.

            Senior Technical Representative

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              Managing Your 3DEXPERIENCE Cache: Keep Your Files Clean and Up to Date

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              Managing Your 3DEXPERIENCE Cache: Keep Your Files Clean and Up to Date

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              One of the biggest advantages of the 3DEXPERIENCE platform is having your files stored securely in the cloud. You can access your designs anytime, anywhere, and collaborate with teammates without worrying about version control.

              Behind the scenes, SOLIDWORKS uses a local cache, a folder on your computer where files are temporarily stored while you work. These cached files are then synced with the 3DEXPERIENCE servers when you save or refresh.

              Managing this cache is key to keeping your designs current, preventing confusion, and saving disk space. Let’s take a closer look.

              Where to Find the 3DEXPERIENCE Cache

              Think of 6W Tags as smart labels that make it easy to filter, sort, and find your files in 3DSpace or 3DDrive.

              Your cache shows up both in SOLIDWORKS (via the 3DEXPERIENCE add-in) and in Windows Explorer. While you can browse the cache folders directly, we don’t recommend managing them that way. Instead, stick to the tools built into SOLIDWORKS.

              Here are the default folder locations:

              • SOLIDWORKS Desktop with the 3DEXPERIENCE add-in:
                C:\3DEXPERIENCE

              • SOLIDWORKS Connected:
                C:\Users\<username>\AppData\Local\DassaultSystemes\3DEXPERIENCE

              Managing the Cache Inside SOLIDWORKS

              When you enable the “3DEXPERIENCE Files on This PC” add-in, you’ll see a dedicated tab in the Task Pane. This view shows you all cached files with helpful details like:

              • Status

              • Lock Status

              • Maturity State

              ub / Managing Your 3DEXPERIENCE Cache

              From here, you can quickly refresh your cache to make sure you’re always working with the latest version.

              • Refresh View updates the local cache for selected files.

              • Refresh from Server checks for changes made by other users and downloads the latest copy if needed.

              • Starting a new SOLIDWORKS session automatically refreshes files in the background.

              ub / Managing Your 3DEXPERIENCE Cache - 2

              Understanding Cache Status Icons

              The status icons make it easy to tell if your local files are current, out-of-date, or waiting to be uploaded. They also warn you if refreshing would overwrite changes you’ve made locally.

              ub / Managing Your 3DEXPERIENCE Cache - Icons

              Pro tip: Always double-check before reloading from the server. Unsaved local edits will be lost.

              Cleaning Up the 3DEXPERIENCE Cache

              Over time, cached files can pile up and take up space. To keep things tidy (and ensure you’re pulling the latest versions from the cloud), it’s a good idea to clean your cache periodically.

              Here’s how:

              1. In the Task Pane, select individual files, or use the top-left checkbox to select all.

              2. Right-click and choose Delete from this PC.”

              ub / Managing Your 3DEXPERIENCE Cache - Delete

              This only removes files from your local cache. Your data stays safe in the 3DEXPERIENCE platform.

              You can also use:

              • Filters to find specific file types.

              • The search box to locate files quickly.

              And before you delete, always confirm your files are saved and synced to the platform.

              Automating Cache Clean-Up

              Don’t want to do it manually? The Clean Up command takes care of it for you.

              • By default, it removes unchanged files older than one week.

              • Locked or modified files won’t be touched.

              • If you open an assembly later, any missing references are automatically redownloaded from the server.

              ub / Managing Your 3DEXPERIENCE Cache - Automation

              If disk space isn’t a concern, you can extend the timeframe to reduce how often files get cleared. It is especially useful if your internet connection is slow.

              A Simple Habit for Staying Up to Date

              The local 3DEXPERIENCE cache is like a bridge between your desktop and the cloud. Keep it clean, refresh it often, and you’ll always know you’re working with the latest designs.

              Want to get even more out of your 3DEXPERIENCE platform? Our training sessions are designed to help you and your team take full advantage of its powerful tools.


              Michael Habrich

              3DEXPERIENCE Specialist

              LinkedIn

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                Make Your Data Work for You with 6W Tags on the 3DEXPERIENCE Platform

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                Make Your Data Work for You with 6W Tags on the 3DEXPERIENCE Platform

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                The 3DEXPERIENCE platform isn’t just about CAD in the cloud. It’s your all-in-one workspace where design, data management, and collaboration come together. Whether you’re sketching with xShape, modeling in xDesign, or connecting to SOLIDWORKS, the platform helps keep everything, and everyone, in sync.
                But let’s be honest: every engineering project generates mountains of data. 3D models, drawings, BOMs, simulations, even invoices and Word docs. It all piles up. The good news? The platform makes it easy to organize and navigate this information with a powerful tool called 6W Tags.

                What Are 6W Tags?

                Think of 6W Tags as smart labels that make it easy to filter, sort, and find your files in 3DSpace or 3DDrive.

                6W Tags in SOLIDWORKS

                And it’s not just CAD data. Office documents, simulation results, and more can all benefit from tagging.

                Here’s how the 6Ws break down:

                • What: Type of content (CAD models, documents, simulations, tasks, etc.)
                • Who: The person who uploaded, edited, revised, or owns the data
                • When: Date or time range
                • Where: Geolocation or data source
                • How: Manufacturing method (made in-house or purchased)
                • Why: Links to project or task management

                Out of the box, the system automatically fills in basics like owner, location, and save date. But the real power comes when your team adds custom tags. For example, you can include project numbers, material types, or vendor names so searches are tailored to your company’s workflow.

                How to Use 6W Tags

                Let’s say you search for “bolt” in 3DEXPERIENCE. Without filters, you might get hundreds (if not thousands) of results. That’s where 6W Tags shine.

                Search bar for 6W Tags in SOLIDWORKS

                Click the tag icon next to the search bar, then start narrowing your results. For example:

                • Under What, choose Physical Product (to exclude tasks or documents).
                • Add a Material filter for Stainless Steel.

                By stacking filters, your results go from overwhelming to precise in just a few clicks.

                Real-World Examples

                In one test, a simple search brought back over 1,000 results. But after filtering with 6W Tags for “Physical Product” and “Plain Carbon Steel,” the number of results dropped down to two digits. That’s the power of smart filtering.

                Beyond search, 6W Tags can be used visually inside apps. For example, parts can be color-coded by material in the graphics area, giving you an instant overview of your design.

                From Data Overload to Data Control

                Data shouldn’t slow you down and with 6W Tags, it won’t. Whether you’re hunting down a single file or organizing entire projects, the 3DEXPERIENCE platform helps you stay in control.

                Want to learn more tips like this? Our experts at Solidxperts can help you get the most out of your 3DEXPERIENCE environment. Reach out anytime or join one of our training sessions!


                Michael Habrich

                3DEXPERIENCE Specialist

                LinkedIn

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                  Organizing and Managing Your SOLIDWORKS Libraries in 3DEXPERIENCE

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                  Organizing and Managing Your SOLIDWORKS Libraries in 3DEXPERIENCE

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                  One of the biggest strengths of the 3DEXPERIENCE platform is how it brings your team together. With SOLIDWORKS Cloud Services, you get built-in data management, making it simple to collaborate with colleagues, keep projects organized, and even access your designs on the go.

                  Whether you’re working in SOLIDWORKS Connected or traditional SOLIDWORKS combined with Collaborative Designer for SOLIDWORKS, you have a direct link to the 3DEXPERIENCE platform, so opening, saving, and managing your model data feels seamless.

                  But here’s the thing: design work goes beyond just parts and assemblies. You also rely on libraries, weldment profiles, sheet metal gauge tables, templates, routing components, and more. Keeping those libraries in sync across your team is just as important as managing your models. And with 3DEXPERIENCE, you can centralize those libraries too.

                  Step 1: Create Your Library Structure

                  Start in the Bookmark Editor app (in your web browser). Create a clean folder structure for your templates and libraries, with subfolders for each type. Then, simply drag and drop your files into place.

                  This way, your team has one organized hub for all shared resources.

                  Step 2: Set Up Weldment Profiles

                  For weldments, it’s best to stick with a consistent naming convention: Standard → Type → Size.

                  We also recommend customizing your standard names to keep them separate from the defaults SOLIDWORKS provides. For example, you might create a standard called “Xperts – ANSI Inch”.

                  Once you’ve named things properly, drag your weldment profile files (or entire folders) from Windows File Explorer directly into your 3DEXPERIENCE bookmark. Quick, easy, and ready to use.

                  Step 3: Connect Libraries to SOLIDWORKS

                  Inside SOLIDWORKS, go to System Options → File Locations. When you add a new location, choose “Select from 3DEXPERIENCE”.

                  This links SOLIDWORKS to your bookmarks, syncing the content down to your local cache (usually found at C:\Users\Public\Documents\SOLIDWORKS). You’ll notice the linked locations show up in brackets, confirming they’re tied to the platform.

                  To make sure you’re always up to date, just click Update. SOLIDWORKS will pull the latest versions from 3DEXPERIENCE, keeping your whole team in sync.

                  Step 4: Keep Your Libraries Updated

                  Need to update a file? Head back into the Bookmark Editor in your browser, right-click the file, and select Update. Browse for the new version locally, and the platform will take care of the rest.

                  Once it’s updated in 3DEXPERIENCE, users just need to hit Update in their SOLIDWORKS options to refresh their local cache. Simple, controlled, and consistent.

                  Why This Matters

                  Storing your libraries and templates alongside your design data gives you the same benefits: revision control, lifecycle management, and a single source of truth for your team.

                  We focused on weldment profiles here, but the same approach works for routing components, sheet metal gauge tables, and more. With SOLIDWORKS Cloud Services + 3DEXPERIENCE, you’re not just managing files. You’re creating a smarter, more connected workflow for your entire team.

                  At Solidxperts, we love helping teams get the most out of their tools. Setting up your libraries in 3DEXPERIENCE is a small step that makes a big impact on collaboration, efficiency, and design quality.


                  Michael Habrich

                  3DEXPERIENCE Specialist

                  LinkedIn

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                    How to Back Up Your 3DEXPERIENCE Data

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                    How to Back Up Your 3DEXPERIENCE Data

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                    Backing up your data is always a smart move. The good news is that the 3DEXPERIENCE platform already includes secure cloud storage, but sometimes you may want to create a local, on-site backup as well.

                    To help you do that, this guide walks you through two options:

                    1. Exporting one project at a time (top-level assembly in its own .zip file)

                    2. Exporting everything together (all data in a single .zip file)

                    Option 1: Export a Single Project

                    This method is perfect if you only need to back up a specific assembly or project.

                    1.Use the search field at the top of your session (or the Bookmark Editor, if you’ve bookmarked the file) to locate your top-level assembly.

                    2. Select the assembly (it will highlight in blue when chosen).

                    3. Click the chevron (arrow) to the right of the file.

                    4. Choose Export As.

                    Choose Export As.

                    5. Continue with the export steps outlined in the final section of this guide.

                    Option 2: Export Everything at Once

                    Heads up: If you have a large dataset, this method can produce a very large zip file. For performance reasons, we often recommend Option 1,  exporting project by project.

                    But if you do want the full export, here’s how:

                    1.Open the Bookmark Editor app.

                    • Create a new bookmark called something intuitive, like Export All Data.
                    • Leave Bookmark Editor open with your new bookmark selected.

                    Open the Bookmark Editor app

                    2. In the search bar, type “prd” (default naming convention).

                    • If your company uses a different convention, use the keyword that applies to your setup (e.g. SX- for Solidxperts).

                    In the search bar, type “prd”

                    3. Optionally, refine results with 6W Tags (Who, What, Where, etc.).

                    4. Select all search results.

                    • Use the checkbox at the top of the list.
                    • Double-check the counter to ensure all items are selected. (If numbers don’t match, scroll to the bottom and re-select.)

                    Select all search results

                    5. Drag the selected files into your export bookmark.

                    • This applies the bookmark to all selected items.
                    • If you have a lot of files, give the system time to process.

                    6. Back in Bookmark Editor, group-select the files you want to export (Ctrl+A for all).

                    7. Click the 3 dots (⋮) in the upper right → choose Export As.

                    Click the 3 dots (⋮) in the upper right → choose Export As

                    8. In the Export As dialog:

                    • Give your .zip file a clear title.
                    • Optionally, check Include Drawing.
                    • Confirm the item count. If it looks low, scroll to the bottom of Bookmark Editor to refresh, then try again.
                    • Review any exclusions in red . These could be xApp-created files (like xDesign) that aren’t currently exportable.

                    9. The system creates an export job.

                    • You can monitor large jobs in the CAD Data Processor Monitoring app.
                    • Smaller jobs often finish before they appear there.

                    The system creates an export job.

                    10. Once complete, you’ll see a notification in the 3DNotification Center.

                    Once complete, you’ll see a notification in the 3DNotification Center.

                    11. Click the notification, then hit Download to retrieve your .zip file.

                    Click the notification, then hit Download to retrieve your .zip file.

                    Pro tip: Test the process with a small dataset first so you’re comfortable before running a full export.

                    Wrapping Up

                    Ultimately, with just a few steps, you can create local backups of your 3DEXPERIENCE projects, whether it’s one assembly at a time or your entire dataset.

                    Beyond the backup process, at Solidxperts, we help teams like yours work more confidently with 3DEXPERIENCE every day. If you’d like hands-on training or tailored backup strategies, our experts are here to guide you.


                    Michael Habrich

                    3DEXPERIENCE Specialist

                    LinkedIn

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