A Novel Modular Disassembly Design Method for CNC Machine Tools based on PSOA and TOPSIS

Abstract

Disassembly is one of the crucial issues for the green remanufacturing of obsolete CNC machine tools. Meanwhile, modular design method is the guarantee of disassembly rationality, which can maximize economic and environmental benefits. However, modular disassembly processes of CNC machine tools are more uncertainty in system structures and component conditions. On the basis of summarizing the existing research, disassembly module modeling of CNC machine tools is implemented. For one advantage, the rough set theory is utilized to cluster the parts into different disassembly modules. For another, disassembly information model is constructed by the disassembly multi-constrained graph. Secondly, multi-objective mathematical model which contains disassembly time, disassembly benefit and disassembly complexity is built. A novel particle swarm optimization algorithm (PSOA) improved by niche technology is applied to the disassembly sequence planning. Last but not least, this work also evaluates the disassembly scheme of CNC machine tools based on the technology for order preference by similarity to an ideal solution (TOPSIS). Evaluation indicator system is established and the comprehensive weight of evaluation indicators is determined by the respective advantages of entropy weight method (EWM) and analytic hierarchy process (AHP). A case study is conducted to illustrate the feasibility of the proposed models and methods. The results of this work can contribute to the selection of the optimal modular disassembly scheme of CNC machine tools.