Fuzzy-Clustering Based Cost Modeling of Disassembly Planning for EOL Products

Zhou Ziqiang*, 1, 2, Dai Guohong1, 2, Wu Zhaoren2, 3, Zhang Xiangyan2, 3
1 School of Mechanical Engineering, Changshu Institute of Technology, Changshu, Jiangsu, 215500, P.R. China
2 Jiangsu Key Laboratory of Recycling and Reuse Technology for Mechanical and Electronic Products (Changshu Institute of Technology), China
3 School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, P.R. China

© 2015 Ziqiang et al

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: ( This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the School of Mechanical Engineering, Changshu Institute of Technology, Changshu, Jiangsu, 215500 Chang; Tel: 86-512-52251595; Fax: 86-512-52251595; E-mail:


Cost model is a key issue in the disassembly process planning, because the optimized disassembly sequence is determined by ranking several possible disassembly operations. In this study, a fuzzy cost model for disassembly processes was developed based on the fuzzy clustering method. The objective was to solve the problems in the practical applications of currently used quantitative models of disassembly cost model, which is based on the change times of the tools operation or the disassembly time. The sample data were obtained through the disassembly tests of the typical EOL (end-of-life) products. Following this , the transitive closure operations were performed after standardization and normalization. Dynamic clustering was carried out on the basis of above results, and appropriate clustering results were selected to construct the membership function of fuzzy costs. This study also proposed a method of proportional interpolation to expand the directly built membership function to the uncovered discourse domain, resulting in more practical fuzzy cost models. Finally, the disassembly process of a general reducer was adopted as an example to verify the feasibility of the above method.

Keywords: Disassembly, Disassembly cost model, Fuzzy clustering, Recycling, Remanufacturing.