An expert system using rough sets theory and self-organizing maps to design space exploration of complex products

  • Authors:
  • Xue-Zheng Chu;Liang Gao;Hao-Bo Qiu;Wei-Dong Li;Xin-Yu Shao

  • Affiliations:
  • The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, 1037, Luoyu Road, Wuhan, Hubei 430074, PR China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, 1037, Luoyu Road, Wuhan, Hubei 430074, PR China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, 1037, Luoyu Road, Wuhan, Hubei 430074, PR China;Department of Engineering and Manufacturing Management, Faculty of Engineering and Computing, Coventry University Priory Street, Coventry CV1 5FB, UK;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, 1037, Luoyu Road, Wuhan, Hubei 430074, PR China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2010

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Abstract

In complex product design, product performance driving design is a new and innovative research in the engineering field. For realizing the product performance driving design, an elaborated expert system, Expert Systems for Assisting Mapping from Performance Space to Design Space (ESMPD) is proposed, which have two main modules for mapping from product performance space to interesting design space by two layers mapping method. In Rough Sets Theory Analysis Module, Rough Sets Theory (RST) is used to calculate configuration rules in incomplete configuration information system to assist product designers in mapping performance space to configuration space. In self-organizing maps Analysis Module, SOM is employed to analyze design variables and objective function based on preliminary optimization, to mapping from the fixed configuration space to smaller interesting regions in design space. The contribution of this research is utilizing the product design knowledge to guide engineer to partition and reduce the design space, which can save product design time and promote the design efficiency. Finally, a new bulk carrier design is taken as a case study to prove the validity and necessity of this expert system. The detailed analysis testifies ESMPD can effectively facilitate rapid and intelligent design, and reduce the cost of complex product design.