A systematic approach in remanufacturing for high efficiency and low cost: The selective parallel disassembly sequence planning. (April 2022)

• Record Type: Journal Article
• Authors: Zhang, Lei; Wu, Yuanfeng; Li, Ziqi; Zheng, Yu; Ren, Yongqiang; Zhu, Libin
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 236:Number 5(2022)
• Page Start: 572
• Page End: 585
• Publication Date: 2022-04
• Subjects: Selective disassembly -- parallel disassembly sequence planning -- multi-objective optimisation -- genetic algorithm (GA) -- remanufacturing; Mechanical engineering -- Periodicals; Engineering -- Management -- Periodicals; Manufacturing processes -- Periodicals; 629.8
• DOI: 10.1177/09544054211041036
• Languages: English
• ISSNs: 0954-4054

Abstract

With the growth of environmental awareness, remanufacturing and sustainable manufacturing have become hot issues. Disassembly is the first step and critical activity in remanufacturing. Traditional disassembly sequence planning (DSP) focusses on sequential disassembly. However, it is inefficient for complicated products because only one manipulator is employed to execute disassembly operations. Thus, this work focusses on parallel DSP (PDSP) and proposes a selective parallel disassembly sequence planning (SPDSP) methodology, which performs disassembly compared to sequential DSP and PDSP. In this paper, a mathematical model is used to describe the constraint and precedence relationships, and a parallel sequence model is designed for parallel disassembly. A novel hybrid genetic algorithm (NHGA) based-multi-objective model of SPDSP is proposed for optimisation. In this model, two indicators are integrated: disassembly time (including basic disassembly time, tool exchange time and direction change time) and disassembly costs. A transmission box is used as an instance, and a comparison with conventional genetic algorithm (GA), simulated annealing (SA) and tabu search (TS) is made to validate the practicality of the proposed methodology.