Disassembly sequence planning using discrete Bees algorithm for human-robot collaboration in remanufacturing

•Human-robot collaborative disassembly is a kind of parallel disassembly, and disassembly tasks are assigned to the operator and the robots according to the difficulty of disassembly tasks.•Disassembly sequence planning for human-robot collaboration is solved by modified discrete Bees algorithm base...

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Veröffentlicht in:Robotics and computer-integrated manufacturing 2020-04, Vol.62, p.101860, Article 101860
Hauptverfasser: Xu, Wenjun, Tang, Quan, Liu, Jiayi, Liu, Zhihao, Zhou, Zude, Pham, Duc Truong
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Sprache:eng
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Zusammenfassung:•Human-robot collaborative disassembly is a kind of parallel disassembly, and disassembly tasks are assigned to the operator and the robots according to the difficulty of disassembly tasks.•Disassembly sequence planning for human-robot collaboration is solved by modified discrete Bees algorithm based on Pareto.•Modified discrete Bees algorithm based on Pareto outperforms the other three optimization problems in solution quality. Remanufacturing helps to improve the resource utilization rate and reduce the manufacturing cost. Disassembly is a key step of remanufacturing and is always finished by either manual labor or robots. Manual disassembly has low efficiency and high labor cost while robotic disassembly is not flexible enough to handle complex disassembly tasks. Therefore, human-robot collaboration for disassembly (HRCD) is proposed to flexibly and efficiently finish the disassembly process in remanufacturing. Before the execution of the disassembly process, disassembly sequence planning (DSP), which is to find the optimal disassembly sequence, helps to improve the disassembly efficiency. In this paper, DSP for human-robot collaboration (HRC) is solved by the modified discrete Bees algorithm based on Pareto (MDBA-Pareto). Firstly, the disassembly model is built to generate feasible disassembly sequences. Then, the disassembly tasks are classified according to the disassembly difficulty. Afterward, the solutions of DSP for HRC are generated and evaluated. To minimize the disassembly time, disassembly cost and disassembly difficulty, MDBA-Pareto is proposed to search the optimal solutions. Based on a simplified computer case, case studies are conducted to verify the proposed method. The results show the proposed method can solve DSP for HRC in remanufacturing and outperforms the other three optimization algorithms in solution quality.
ISSN:0736-5845
1879-2537
DOI:10.1016/j.rcim.2019.101860