Optimization to identify the adapted product design and product adaptation process with initial evaluation of information quality in branches of AND-OR tree based on information entropy

Abstract

Adaptable products are used to satisfy new customer requirements through changes of products such as upgrading of modules during their utilization stages. Compared with the creation of a new product from scratch, the process to adapt an existing product to a new one can result in savings for the customer. In this research, a new optimization approach to identify the adapted product design and product adaptation process is developed with initial evaluation of information quality in branches of AND-OR tree based on information entropy. In this approach, various candidates of design configurations and operation processes for adaptation of a product are modelled by an AND-OR tree with design and process nodes. Design and process nodes are further associated with design and process parameters. Optimization to identify the best adapted design and adaptation process is conducted at two levels: configuration/process optimization level and parameter optimization level. Information entropy is employed to evaluate the information quality of partial configuration/process candidates modelled as branches in the AND-OR tree to eliminate the branches that are unlikely to lead to the optimal solution for improvement of the optimization efficiency. A numerical example and an engineering application are developed to demonstrate the effectiveness of the newly introduced approach.