Industrial Engineering Journal ›› 2023, Vol. 26 ›› Issue (4): 144-153.doi: 10.3969/j.issn.1007-7375.2023.04.017

• System Modeling & Optimization Algorithm • Previous Articles     Next Articles

Flexible Scheduling of Decommissioned Product Disassembly under Uncertain Conditions

MA Xinyi1,3, KUANG Zengyu1, ZHUO Xiaojun2, REN Yinghui1   

  1. 1. College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China;
    2. Changsha Research Institute of Mining and Metallurgy Co., Ltd, Changsha 410012, China;
    3. School of Mechanical Engineering, Tongji University, Shanghai 201804, China
  • Received:2022-08-31 Published:2023-09-08

Abstract: Due to the uncertain differences in the source, types, structures and performance residuals of the recycled decommissioned products, the stationary of disassembly reverse production scheduling before their echelon utilization or resource reuse is affected by uncertainties such as incoming materials, disassembly sequences and disassembly modes. This paper takes disassembly production lines of decommissioned products with flexible fixture workstations as the study object. Considering the disturbance factors caused by uncertain incoming materials, disassembly sequences and disassembly modes, an AND/OR node network scheduling strategy is constructed with the objective of minimizing completion time, and the corresponding mixed integer programming scheduling model is established. The improved simulated annealing parthenogenetic algorithm is adopted to solve it. Results show that compared with traditional manual experience scheduling, the dynamic scheduling strategy and model proposed in this paper can reduce the fluctuation caused by uncertain disturbance factors during production scheduling. Also, the proposed mehtod can effectively balance and improve the utilization of flexible disassembly lines′ equipment and improve the efficiency of decommissioned product disassembly.

Key words: production scheduling, decommissioned products, recycling and disassembling, uncertainty, AND/OR node model

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