Fuzzy Topsis Decision Method for Configuration Management


  • Shu-Hsuan Chang National Changhua University of Education
  • Hwai-En Tseng National Chin-Yi University of Technology




Mass customization, Configuration management, QFD, Fuzzy set theory, TOPSIS


Mass customization refers to an environment in which reducing quantities and increasing varieties of products are being manufactured. A product configuration is defined as an aggregation of parts whose functions and performance parameters must be defined and controlled to achieve the overall performance of a system or product. Since the product configurations would be varied based on consumer needs, selecting effective product configurations from among several alternatives is a challenge during the mass customization design stage. This study developed a structural model which combines a fuzzy quality function deployment with a fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to solve this problem. The configuration alternatives ranked using the proposed method can provide a useful reference for decision makers in implementing configuration management.

Author Biographies

Shu-Hsuan Chang, National Changhua University of Education


Hwai-En Tseng, National Chin-Yi University of Technology

Hwai-En Tseng is currently a professor and the chairman in the Department of Industrial Engineering and Management at National Chin-Yi University of Technology, Taiwan. He has a B.E. in Industrial Design and a M.S. in Mechanical Engineering from National Cheng Kung University, respectively. Finally, he received his Ph.D. degrees in Industrial Engineering and Management from National Chiao Tung University. He also has many years of practical work experience in the Taiwan's Industrial Technology Research Institute. His research activities include assembly/disassembly planning, product knowledge management and mass customization.




How to Cite

Chang, S.-H., & Tseng, H.-E. (2022). Fuzzy Topsis Decision Method for Configuration Management. International Journal of Industrial Engineering: Theory, Applications and Practice, 15(3), 304–313. https://doi.org/10.23055/ijietap.2008.15.3.147



Production Planning and Control