More Possibilities for Virtual Geometric Assurance

CAE More Possibilities for Virtual Geometric Assurance

2025-06-03 From Invenio | Translated by AI 1 min Reading Time

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Disassemble component conflicts instead of overlooking them, ensure data flow instead of risking it: That is what Invenio Virtual Technologies promises with the release of VT-DMU 5.8 and Quality Monitor 6.2.

The VT-DMU 5.8 software identifies related collisions even more precisely.(Image: Invenio) — The VT-DMU 5.8 software identifies related collisions even more precisely.
(Image: Invenio)

Invenio Virtual Technologies GmbH has rolled out the latest versions of the modular software suite VT-DMU and the AI-supported software Quality-Monitor, which cover the entire process of virtual geometric validation. The update package focuses on performance optimizations, maximum clarity in complex assemblies, automated data validation, and configurable visualizations.

Complex Conflicts Presented Transparently

A highlight of the new version is the update of the integrated analysis module 'Decompose'. The algorithm automatically detects connected collisions more precisely and logically breaks them down into individual conflict areas. A real-world application: A wiring harness passing through multiple installation space boundaries often creates numerous geometric issues with sheets, clips, or grommets. VT-DMU now identifies these as independent conflicts, including their own visualization and more precise AI assessment. The result: greater clarity, less rework, and more reliable decisions.

AI Now Knows Which Data is Needed

With the new version of the Quality-Monitor, an important practical goal is achieved: automated checks ensure a constant data basis for AI, so the AI never runs out of input. The tool now independently recognizes whether all necessary and additional information is present—a true efficiency gain in preparing 3D data for AI training, it says. Only valid and fully verified data enter the pipeline, which reduces error rates and increases the success rate in machine learning.

Another advantage: Each geometric conflict is now automatically exported by the AI as a high-resolution single image with individually adjustable section line thickness and color through improved camera positions. The visualizations have been specifically optimized, making AI-generated images even more informative. Invenio VT is currently the only provider with this technology—a unique selling point that has been consistently further developed. Users can recognize even more quickly and intuitively at a glance what the specific problem is.

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