Evaluation and selection in product design for mass customization: A knowledge decision support approach

Mass customization has been identified as a competitive strategy by an increasing number of companies. Family-based product design has been recognized as an efficient and effective means to realize sufficient product variety to satisfy a range of customer demands in support for mass customization. This paper presents a knowledge decision support approach to product family design evaluation and selection for mass customization process. In the paper, product family design is viewed as a selection problem with major stages: product family (design alternatives) generation and product family design evaluation and selection for customization. First, the fundamental issues underlying product family design for mass customization are discussed. Then, a knowledge support framework and its relevant technologies are developed for modulebased product family design for mass customization. A systematic fuzzy clustering and ranking model is proposed and discussed in detail to model imprecision inherent in decision-making with fuzzy customers’ preference relations and carry out fuzzy analysis and evaluation and selection of product family for customization. Neural network technique is also adopted to adjust the membership function to enhance the model. The focus of this paper is on the development of a knowledge intensive support scheme and a comprehensive systematic fuzzy clustering and ranking methodology for product family design evaluation and selection. A case study and the scenario of knowledge support for power supply product evaluation, selection, and customization are provided for illustration.