Balancing manual mixed-model assembly lines using overtime work in a demand variation environment

Balancing manual mixed-model assembly lines using overtime work in a demand variation environment
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在需求变化环境中使用加班来平衡手动混合模型装配线

DOI:
10.1080/00207543.2013.874603
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发表时间:
2014-04
影响因子:
9.2
通讯作者:
Jie Gao
Jie Gao
中科院分区:
工程技术2区
文献类型:
--
作者:
Jinlin Li;Jie Gao

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研究了一条人工混流装配线的平衡问题,其中生产量或产品组合在计划周期内随班次变化。不稳定的需求可以由几个具有代表性的场景来表征,该生产线使用加班来满足需求变化。平衡问题涉及如何将装配任务分配给工位,并确定在每个可能的需求场景中的加班量。目标是满足每一种可能的情况下的需求,同时为正常轮班和加班工作支付最低的劳动力成本。给出了人工成本的一个下界,并开发了一个启发式算法来快速找到可行解。然后提出了一种分支、定界和记忆(BB&R)算法来寻找更好的解。这些求解方法在765个实例上进行了测试。BB&R算法能够获得510个实例的最优解,并为60 S内剩余的255个实例提供高质量的解。实验结果表明,使用超时工作和可调的周期时间显著降低了人工成本,特别是在需求或任务处理时间变化较大的情况下。
This study deals with the balancing problem of a manual mixed-model assembly line, where the production volume or the product mix changes from shift to shift during the planning horizon. The unstable demand can be characterised by several representative scenarios, and the line uses overtime work to meet the demand variation. The balancing problem concerns how to assign assembly tasks to stations and determine the amount of overtime in each possible demand scenario. The objective is to satisfy the demand in each possible scenario with the minimum labour costs paid for both normal shifts and overtime work. A lower bound on the labour costs is proposed, and a heuristic algorithm is developed to quickly find a feasible solution. A branch, bound and remember (BB&R) algorithm is then proposed to find better solutions. These solution methods are tested on 765 instances. The BB&R algorithm obtains optimal solutions for 510 instances and gives high-quality solutions for the remaining 255 instances within 60 s. The experimental results show that the use of overtime work and adjustable cycle times significantly reduces the labour costs, especially when the demand or task processing time variations are large.
DOI: 10.1287/mnsc.14.2.b59
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