Rapid identification of the optimal product configuration and its parameters based on customer-centric product modeling for one-of-a-kind production

One-of-a-kind production (OKP) aims at manufacturing products based on the individual customer requirements while maintaining the high quality and efficiency of mass production. This paper presents a customer-centric product modeling scheme to model OKP product families by considering the relations between customer needs and OKP products. In this modeling scheme, an OKP product family is modeled by an AND-OR tree. In order to investigate the relations between customer needs and OKP products, data mining techniques are employed to achieve knowledge from the historical data. First, OKP products and customer requirements are grouped into product patterns and customer patterns, respectively, using a fuzzy pattern clustering method. Then, hybrid attribute reduction is carried out based on rough set theory to remove the irrelevant attributes for each product pattern. Finally, the relationships between product patterns and customer patterns are obtained. Based on the achieved knowledge, the different patterns of OKP products are modeled by different sub-AND-OR trees trimmed from the original AND-OR tree. Since only partial product descriptions in a product family are used to identify the optimal custom product based on customer requirements, the efficiency of custom product identification process can be improved considerably.