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Operator Scheduling Under the Lean Manufacturing Principles in Over-Size Product Manufacturing Facilities

机译:经营者在超尺寸产品制造设施中按精益制造原则调度

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This paper discusses the scheduling of operators on work elements in manufacturing environments where lean principles are adopted. Our experience with the industry revealed that the practice of lean manufacturing in organizations that manufacture oversized products, such as buses, aircrafts and locomotives differs from other organizations. The most obvious two differences are: the longer Takt times (average time between demands); and the fact that the work-stations are mainly placed in various locations inside/around the product and the operators can carryout activities in parallel in these work stations. Since the demand for the large products is considerably low, Takt time (average time between demands) is usually in the orders of hours. As a result, a product undergoes several modifications during a Takt time. The assembly process of the oversized products involves coordinated work of a number of tasks. While some of the tasks have strict precedence relationship with other activities, the others can be performed simultaneously. In this context, our problem is to assign N different operators to M different tasks with two alternative objectives; minimizing the discrepancies between the operators' workloads and minimizing the number of operators used. The main constraint is to complete all the tasks within a given Takt time. We modeled the problem under both identical operator and non-identical operator assumptions. Various sensitivity analyses are discussed and the several examples are provided.
机译:本文讨论了采用精益原则的制造环境中运营商的运营商调度。我们与该行业的经验透露,在制造超大产品的组织中精益制造的实践,例如公共汽车,飞机和机车等来自其他组织的差异。最明显的两种差异是:Takt时间越长(需求之间的平均时间);而且工作站主要被置于产品内/周围的各个位置,操作员可以在这些工作站中并行进行活动。由于对大型产品的需求相当低,TAGT时间(需求之间的平均时间)通常是数小时的订单。结果,产品在TAB时经历了几种修改。超大产品的装配过程涉及多项任务的协调工作。虽然一些任务与其他活动有严格的优先关系,但其他任务可以同时执行其他任务。在这种情况下,我们的问题是将N个不同的运营商分配给具有两个替代目标的不同任务;最小化运营商工作负载之间的差异,最大限度地减少使用的运算符数量。主要约束是在给定的时间内完成所有任务。我们以相同的运算符和非相同的运算符假设为解决问题。讨论了各种敏感性分析,提供了几个例子。

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