Integrating rough set clustering and grey model to analyse dynamic customer requirements

Customer requirements analysis is of critical importance in design for mass customization. The present paper investigates two important issues in customer requirements analysis. The first is clustering for the customer requirements and the product features (functional requirements), and the consistency analysis approach is applied to link customer groups with clusters of product features. The second issue concerns trends analysis of dynamic customer requirements and functional requirements on the basis of consistency analysis of customer groups and product feature clusters. A novel methodology integrating popular clustering techniques (such as fuzzy clustering and rough set) and grey theory is proposed for accomplishing the two tasks. It focuses on customer group based knowledge of customer requirements from the transaction records. This is used to provide decision support for product development by analysing historical data. A case study is presented to illustrate the proposed method.

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