Machine learning-based part determinations for computer-aided design (cad) assemblies
AssigneeSiemens Industry Software Inc.
InventorsMatthew McMinn, Neeraj Panhalkar, Mohsen Rezayat
Life of this patent
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AssigneeSiemens Industry Software Inc.
InventorsMatthew McMinn, Neeraj Panhalkar, Mohsen Rezayat
Estimating the term…
A computing system may include an assembly access engine configured to access a computer-aided design (CAD) assembly that digitally represents a product component that includes multiple parts. The computing system may also include a part determination engine configured to determine a recommended part for the CAD assembly, including by providing the CAD assembly as an input to a machine-learning (ML) model trained with assembly structure data of CAD assemblies of a common product type as the CAD assembly, generating a candidate part set through the ML model, filtering the candidate part set based on physical and cost characteristics of the different candidate parts of the candidate part set, and identifying the recommended part from the filtered candidate part set. The part recommendation engine may also be configured to insert the recommended part into the CAD assembly and provide the CAD assembly in support of physical manufacture.
A method comprising:
A system comprising:
A non-transitory machine-readable medium comprising instructions that, when executed by a processor, cause a computing system to:
Dependencies are inferred from the claim text.