Determining component part combination using artificial intelligence

A system, comprising:

• one or more computer readable storage media storing program instructions;
• and
• one or more processors which, in response to executing the program instructions, are configured to:
• train an artificial intelligence model to learn failure patterns associated with component part combinations for an end-product, wherein the training configures the artificial intelligence model to determine component parts for a component part combination that reduce a probability of end-product failure attributable to the component part combination;
• obtain measurement data for groups of component parts configured to be assembled as part of an end-product, wherein the measurement data comprises measurement specifications and actual measurements for interfacing portions of component parts included in the groups of component parts;
• obtain specification scores for the component parts included in the groups of component parts, wherein the specification scores are based at least in part on the measurement specifications and the actual measurements for the interfacing portions of the component parts;
• input the specification scores for the component parts to the artificial intelligence model to select a component part combination from the groups of component parts, wherein the artificial intelligence model evaluates the specification scores against the learned failure patterns to determine that the component part combination decreases a probability of a product failure as compared to historical occurrences of end-product failures attributable to other component part combinations;
• and
• output information for at least one component part included in the component part combination to an automated system, wherein responsive to receiving the information, the automated system retrieves the at least one component part for assembly of the end-product.

A computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising instructions configured to cause one or more processors to:

• train an artificial intelligence model to learn failure patterns associated with component part combinations for an end-product, wherein the training configures the artificial intelligence model to determine component parts for a component part combination that reduce a probability of end-product failure attributable to the component part combination;
• obtain measurement data for groups of component parts configured to be assembled as part of an end-product, wherein the measurement data comprises measurement specifications and actual measurements for interfacing portions of component parts included in the groups of component parts;
• obtain specification scores for the component parts included in the groups of component parts, wherein the specification scores are based at least in part on the measurement specifications and the actual measurements for the interfacing portions of the component parts;
• input the specification scores for the component parts to the artificial intelligence model to select a component part combination from the groups of component parts, wherein the artificial intelligence model evaluates the specification scores against the learned failure patterns to determine that the component part combination decreases a probability of a product failure as compared to historical occurrences of end-product failures attributable to other component part combinations;
• and
• output information for at least one component part included in the component part combination to an automated system, wherein responsive to receiving the information, the automated system retrieves the at least one component part for assembly of the end-product.