Multi-objective human-robot collaborative disassembly line balancing considering components remanufacture demand and hazard characteristics

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Industrial Engineering Pub Date : 2024-10-09 DOI:10.1016/j.cie.2024.110621
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Abstract

Disassembly enterprises face significant challenges in managing increasingly intensive workloads with a workforce alone. To address this, current study focuses on balancing a human-robot collaborative disassembly line. For the task operator allocation problem, a mapping constraint mechanism between the disassembly tasks and the task operators is established based on the remanufacture demand and hazard characteristics of components. A mixed-integer programming model is formulated, encompassing four optimization objectives: the number of workstations, the task operator idle balancing index, the demand index, and the hazard index. A novel modified teaching and learning optimization approach is proposed for the addressed human-robot collaborative disassembly line balancing problem. A two-layer encoding strategy is designed based on the solving characteristics of the problem and an embedded perturbation strategy based on randomly transforming the task operator is introduced to enhance the optimization performance of the proposed method. The validity of the mixed-integer programming model and the efficacy of the proposed algorithm are demonstrated through two small-scale human-robot collaborative disassembly case studies. The proposed algorithm is then applied to two real-life cases of human-robot collaborative disassembly lines with different scales. The results of the proposed optimization method are compared with other advanced algorithms, demonstrating its superior performance in both single-objective and multi-objective optimization based on multiple evaluation indicators.
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考虑部件再制造需求和危险特性的多目标人机协作拆卸线平衡
拆卸企业在仅靠劳动力管理日益密集的工作量方面面临巨大挑战。为解决这一问题,当前的研究侧重于平衡人机协作拆卸生产线。针对任务操作员分配问题,基于再制造需求和部件的危险特性,建立了拆卸任务和任务操作员之间的映射约束机制。混合整数编程模型包括四个优化目标:工作站数量、任务操作员空闲平衡指数、需求指数和危险指数。针对所解决的人机协作拆卸线平衡问题,提出了一种新颖的修正教学优化方法。根据问题的求解特点设计了双层编码策略,并引入了基于随机变换任务算子的嵌入式扰动策略,以提高所提方法的优化性能。通过两个小型人机协作拆卸案例研究,证明了混合整数编程模型的有效性和所提算法的有效性。然后将所提出的算法应用于两个不同规模的人机协作拆卸生产线的实际案例。将所提优化方法的结果与其他先进算法进行了比较,证明了其在基于多个评价指标的单目标和多目标优化中的优越性能。
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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