Mass customization has been identified as a competitive strategy by
an increasing number of companies. Family-based product design is an
efficient and effective means to realize sufficient product variety,
while satisfying 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. Here, product family design is viewed as a
selection problem with the following stages: product family (design
alternatives) generation, product family design evaluation, and
selection for customization. The fundamental issues underlying product
family design for mass customization are discussed. Then, a knowledge
support framework and its relevant technologies are developed for
module-based product family design for mass customization. A systematic
fuzzy clustering and ranking model is proposed and discussed in detail.
This model supports the imprecision inherent in decision making with
fuzzy customers' preference relations and uses fuzzy analysis
techniques for evaluation and selection. A 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
family evaluation, selection, and customization are provided for