• Partfinder for Additive Manufacturing

    Partfinder for Additive Manufacturing Find your parts for 3D Printing automatically

Automatic identification of 3D printing components

With the Partfinder CAD data of all common formats can be analysed, sorted and also converted automatically for different 3D printing processes and machine types.
The web interface of the Partfinder Manager allows flexible use in corporate networks and the native scripting language an easy integration into PLM systems. The multiprocessor calculation or cluster calculation allows an unrivaled fast analysis and/or conversion of large amounts of data.
3D_Evolution Partfinder comes with sophisticated interfaces for CATIA, NX, SOLIDWORKS, Creo, JT, STL, STEP, XT, Acis and many more enabeling a superfadst and highly precise batch conversion. The data can be saved for 3D printing in amf, 3mf and STL format. Sophisticated interfaces and analysis functions ensure that optimal quality and watertight" models are generated.

Test profiles for analysis and sorting

With the Partfinder, CAD data of all formats can be analyzed automatically with regard to the various additive manufacturing processes. The 3D models are geometrically analyzed and, in addition attributes contained in the data, e.g. Material information is used to classify each part.

All analyzes can be summarized in user definable test profiles and run in batch mode over a large number of models, so that even very large databases can be sorted automatically for Additive Manufacturing processes. Our native interfaces read out the attributes and metadata within milliseconds, enabling pre-sorting. Automatic 3D geometry analysis such as calculation of the bounding box, surfaces and volumes provides further important aspects for the automatic classification of the parts.

Advanced analysis such as wall thickness checks or the detection of small holes and other details can be used to identify critical areas for specific processes. Furthermore, the internal backlash check and undercut analysis allow to identify problem areas or models with particularly good 3D printing potential. In the interplay of all functions and the intelligent scripting language, 3D models can be pre-sorted quickly and easily.

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