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A hierarchical heuristic approach for machine loading problems in a partially grouped environment

机译:在部分分组的环境中解决机器负载问题的分层启发式方法

摘要

The loading problem in a Flexible Manufacturing System (FMS) lies in the allocation of operations and associated cutting tools to machines for a given set of parts subject to capacity constraints. This dissertation proposes a hierarchical approach to the machine loading problem when the workload and tool magazine capacity of each machine are restrained. This hierarchical approach reduces the maximum workload of the machines by partially grouping them. This research deals with situations where different groups of machines performing the same operation require different processing times and this problem is formulated as an integer linear problem. This work proposes a solution that is comprised of two phases. In the first phase (Phase I), demand is divided into batches and then operations are allocated to groups of machines by using a heuristic constrained by the workload and tool magazine capacity of each group. The processing time of the operation is different for each machine group, which is composed of the same identical machines; however, these machines can perform different sets of operations if tooled differently. Each machine and each group of machines has a limited time for completing an operation. Operations are allocated to groups based on their respective workload limits. In the second phase (Phase II), demand is divided into batches again and operations are assigned to machines based on their workload and tool magazine capacity defined by Longest Processing Time (LPT) and Multifit algorithms. In Phase II, like Phase I, partial grouping is more effective in balancing the workload than total grouping. In partial grouping, each machine is tooled differently, but they can assist one another in processing each individual operation. Phase I demonstrates the efficiency of allocating operations to each group. Phase II demonstrates the efficiency of allocating operations to each machine within each group. This two-phase solution enhances routing flexibility with the same or a smaller number of machines through partial grouping rather than through total grouping. This partial grouping provides a balanced solution for problems involving a large number of machines. Performance of the suggested loading heuristics is tested by means of randomly generated tests.
机译:柔性制造系统(FMS)中的加载问题在于,对于受能力限制的给定一组零件,将操作和相关的切割工具分配给机器。针对每台机器的工作量和刀库容量受到限制的情况,本文提出了一种分层的解决方法。这种分层方法通过对机器进行部分分组来减少机器的最大工作量。这项研究处理的情况是,执行相同操作的不同机器组需要不同的处理时间,并且此问题被表述为整数线性问题。这项工作提出了一个包含两个阶段的解决方案。在第一阶段(第一阶段),将需求分为几批,然后通过使用受每组工作量和刀具库容量限制的启发式方法,将操作分配给各组机器。每个机器组(由相同的相同机器组成)的操作处理时间不同。但是,如果使用不同的工具,则这些机器可以执行不同的操作集。每台机器和每组机器都有有限的时间来完成操作。根据其各自的工作量限制将操作分配给组。在第二阶段(第二阶段)中,将需求再次分为批次,并根据机器的工作量和由最长处理时间(LPT)和Multifit算法定义的工具库容量,将操作分配给机器。在第二阶段中,与第一阶段一样,部分分组在平衡工作负载方面比总分组更有效。在部分分组中,每台机器的工具使用不同,但是它们可以互相协助来处理每个单独的操作。第一阶段演示向每个组分配操作的效率。第二阶段演示了将操作分配给每个组中每台计算机的效率。此两阶段解决方案通过部分分组而不是通过整体分组来增强相同或更少数量机器的路由灵活性。这种部分分组为涉及大量机器的问题提供了一种平衡的解决方案。建议的加载启发式方法的性能通过随机生成的测试进行测试。

著录项

  • 作者

    Lee Jong Hwan;

  • 作者单位
  • 年度 2004
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  • 原文格式 PDF
  • 正文语种 en_US
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