Configurable product return determination using computational modeling

A computer system comprising:

• a memory;
• and
• a processor in communication with the memory, wherein the computer system is configured to perform a method comprising:
• maintaining product profiles of a plurality of products, wherein the plurality of products includes respective components, and wherein the product profiles indicate updated configurations of the plurality of products, including updated configurations of the respective components of the plurality of products;
• building and training a set of models based on at least some of the maintained product profiles, the set of models configured to perform:
• identifying products that are expected to be returned in the future;
• predicting retention times for products that are expected to be returned in the future;
• and
• determining, based on quality indicators of products that are expected to be returned in the future and on requirements for reusability of components, reusable components of products that are expected to be returned in the future;
• and
• using the set of models and a product profile, of the maintained product profiles, of a product in use, the product in use comprising a set of components and the product profile indicating a current configuration of the product in use, including a current configuration of the set of components:
• determining that the product in use is expected to be returned in the future and an expected timeframe of the return of the product in use;
• and
• determining one or more components, of the set of components of the product in use, that are reusable upon return of the product in the future.

A computer program product comprising:

• a computer readable storage medium readable by a processing circuit and storing instructions for execution by the processing circuit to:
• maintain product profiles of a plurality of products, wherein the plurality of products includes respective components, and wherein the product profiles indicate updated configurations of the plurality of products, including updated configurations of the respective components of the plurality of products;
• build and train a set of models based on at least some of the maintained product profiles, the set of models configured to perform:
• identifying products that are expected to be returned in the future;
• predicting retention times for products that are expected to be returned in the future;
• and
• determining, based on quality indicators of products that are expected to be returned in the future and on requirements for reusability of components, reusable components of products that are expected to be returned in the future;
• and
• use the set of models and a product profile, of the maintained product profiles, of a product in use, the product in use comprising a set of components and the product profile indicating a current configuration of the product in use, including a current configuration of the set of components, to:
• determine that the product in use is expected to be returned in the future and an expected timeframe of the return of the product in use;
• and
• determine one or more components, of the set of components of the product in use, that are reusable upon return of the product in the future.