Machine learning-based generation of constraints for computer-aided design (cad) assemblies

A system comprising:

• a constraint learning engine configured to:
• access a computer-aided design (CAD) assembly comprising multiple CAD parts;
• generate a representation graph of the CAD assembly, wherein nodes in the representation graph represent geometric faces of the multiple CAD parts and edges in the representation graph represent geometric edges of the multiple CAD parts;
• determine constraints in the CAD assembly, wherein the constraints limit a degree of movement between geometric faces of different CAD parts in the CAD assembly;
• insert constraint edges into the representation graph that represent the determined constraints;
• and
• provide the representation graph as training data to train a machine-learning model;
• and
• a constraint generation engine configured to generate constraints for a different CAD assembly by applying the machine-learning model for the different CAD assembly.

A non-transitory machine-readable medium comprising instructions that, when executed by a processor, cause a computing system to:

• access a computer-aided design (CAD) assembly comprising multiple CAD parts;
• generate a representation graph of the CAD assembly, wherein nodes in the representation graph represent geometric faces of the multiple CAD parts and edges in the representation graph represent geometric edges of the multiple CAD parts;
• determine constraints in the CAD assembly, wherein the constraints limit a degree of movement between geometric faces of different CAD parts in the CAD assembly;
• insert constraint edges into the representation graph that represent the determined constraints;
• provide the representation graph as training data to train a machine-learning model;
• and
• generate constraints for a different CAD assembly by applying the machine-learning model for the different CAD assembly.