|
Abstract: Module-based product family design is the key support technology in design for mass customization (DFMC). In order to speed up the response to the changing customer requirements, a novel approach to predicting new configurational product variants is proposed based on the integration of rough set and neural network through discovering the knowledge for the historical configuration information. A hierarchy model of module-based product family and the corresponding formal description are presented. Additionally, the prediction framework is proposed. The methodology can reuse the discovered configuration rules and knowledge efficiently, as well as reduce the effort of experimental measurement to some extent. The prediction values can be regarded as the indices for the customer satisfactions. Finally, the model is verified on a newly developed refrigerator family.
Key words: Rough set Neural network
Module-based product family Prediction
Mass customization Configuration
CLC No: TH122
国家自然科学基金(50575084, 50675082)和国家重点基础研究发展计划(973计划, 2004CB719405)资助项目. Received 20060627, received in revised form 20061229
|