The French start-up Fairwik has presented a new solution with the MecAgent project, which is based on machine learning and automates the creation of parametric components. The target group are engineers and product designers who want to implement complex mechanical designs more efficiently. The agent is designed to automatically generate CAD models based on technical specifications, which can then be used directly.
The system is based on a combination of geometric context, online databases and the company’s own file access. In the first step, MecAgent recognizes relevant axes, surfaces or interfaces in an assembly. The agent then suggests suitable designs, optimized for various manufacturing methods such as CNC milling or 3D printing. Price estimates for various materials are also integrated. This eliminates a large part of the iterative modeling process for users.
In addition, MecAgent searches over 18 online catalogs for standard parts, such as ball bearings, and can automatically identify components from a company’s internal file system – even if they are inadequately named or poorly stored. This function acts as an AI-supported search engine for technical files and simplifies the reuse of existing resources.
Another use case is the direct editing of component geometries. Users can add freehand sketches to the model, which MecAgent converts into functional solids. Changes to the geometry are checked automatically, whereby conflicts with internal company standards are recognized and explained by linking to the appropriate documentation.
The tool offers three options for further processing: direct dispatch to certified partners, integration into in-house production chains or an automated online supplier search. MecAgent is currently in the beta phase. The tool can be tested at mecagent.com.
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