Selection of modules for mass customisation

Abstract

Satisfying customer expectations is of paramount importance in today's markets. A customer expects to receive a product that meets as best as possible his/her expectations. To satisfy diversified requirements companies may focus on product families. For a specific customer the company has to select within a product family what will make a valid product. Then, in a just-in-time environment, the suppliers may have to provide the exact subassemblies corresponding to each product in a predefined time. This integration takes place by designing modules for the supplier. This paper proposes to extract customers’ behaviour patterns, in terms of the components required, using data-mining and entropy maximisation when selecting modules to be manufactured. Different methods for selection of modules are proposed. Computational tests are performed to evaluate performance of the selection methods with respect to the specified assembly time/resource level.

Keywords:

• modular design
• mass customisation
• assemble-to-order
• data mining
• customer demand
• pattern extraction
• entropy maximisation