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首页> 外文期刊>International Journal of Production Research >Multi-period operator assignment considering skills, learning and forgetting in labour-intensive cells
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Multi-period operator assignment considering skills, learning and forgetting in labour-intensive cells

机译：考虑劳动密集型单元中的技能，学习和遗忘的多时期操作员分配

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This paper deals with assigning operators to various operations in a labour-intensive cellular environment. The operator skill levels and skill-based operation times are used as opposed to the classical approach of using standard times. A three-phase approach is developed to tackle the entire problem: (1) finding alternative cell configurations; (2) loading cells and finding crew sizes; (3) assigning operators to operations. A multi-period analysis is performed to study the main issues in this paper. Mathematical models are used in all phases. Two heuristic approaches (Max, MaxMin) are developed for operator assignment in phase III. Both heuristics are compared and their impact on operator learning and forgetting is also investigated. Results show that the proposed approaches in operator assignment outperform the classical approach of using standard times. Heuristic Max resulted in lower makespan and higher idle times whereas heuristic MaxMin improved operator skills more uniformly.
机译：本文涉及在劳动密集型蜂窝环境中为运营商分配各种操作。与使用标准时间的经典方法相反，使用了操作员的技能水平和基于技能的操作时间。开发了一种分三个阶段的方法来解决整个问题：（1）查找备用单元配置； （2）装载牢房并找到船员人数； （3）指定操作员进行操作。进行了多周期分析以研究本文的主要问题。在所有阶段都使用数学模型。在第三阶段，开发了两种启发式方法（Max，MaxMin）用于操作员分配。比较了两种启发式方法，还研究了它们对操作员学习和遗忘的影响。结果表明，所提出的操作员分配方法优于使用标准时间的经典方法。启发式Max可以缩短制造时间并延长闲置时间，而启发式MaxMin可以更均匀地提高操作员技能。

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