One-of-a-kind production (OKP) is a new manufacturing paradigm to produce customized products based on requirements of individual customers while maintaining the quality and efficiency of mass production. In this research, a customer-centric product modeling scheme is introduced to model OKP product families by incorporating the customer information. To develop this modeling scheme, data mining techniques, including fuzzy pattern clustering method, and hybrid attribute reduction method, are employed to achieve the knowledge from the historical data. 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. A case study to identify the optimal configuration and parameters of window products in an industrial company is used to demonstrate the effectiveness of the introduced approach.

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