US Patent Application 17659904. OPTIMIZED HARDWARE PRODUCT RETURNS FOR SUBSCRIPTION SERVICES simplified abstract

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OPTIMIZED HARDWARE PRODUCT RETURNS FOR SUBSCRIPTION SERVICES

Organization Name

Dell Products L.P.


Inventor(s)

Bijan Kumar Mohanty of Austin TX (US)


Dhilip Kumar of Bangalore (IN)


Sujit Kumar Sahoo of Bangalore (IN)


Hung Dinh of Austin TX (US)


OPTIMIZED HARDWARE PRODUCT RETURNS FOR SUBSCRIPTION SERVICES - A simplified explanation of the abstract

  • This abstract for appeared for US patent application number 17659904 Titled 'OPTIMIZED HARDWARE PRODUCT RETURNS FOR SUBSCRIPTION SERVICES'

Simplified Explanation

This abstract describes a methodology for a product subscription service. The service receives information about a hardware asset that is being returned at the end of a subscription. It uses a machine learning model to predict whether the hardware asset has reached its end of life (EOL). If it predicts that the asset has reached EOL, it creates a work order to dispatch an eco-partner. If it predicts that the asset has not reached EOL, it uses another machine learning model to predict new subscription orders that match the hardware asset and recommends these as possible fits for the asset.


Original Abstract Submitted

In one aspect, an example methodology implementing the disclosed techniques includes, by a product subscription service, receiving information regarding a hardware asset being returned at an end of a subscription and predicting, using a first machine learning (ML) model, whether the hardware asset has reached EOL. The method also includes, responsive to predicting that the hardware asset has reached EOL, creating, by the product subscription service, a work order to dispatch an eco-partner. The method may further include, by the product subscription service, responsive to predicting that the hardware asset has not reached EOL, predicting, using a second ML model, one or more new subscription orders matching the hardware asset and recommending the one or more matching new subscription orders as possible fits for the hardware asset.

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