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Decision Support System (DSS) for Machine Selection: A Cost Minimization Model

机译:机器选择的决策支持系统(DSS):成本最小化模型

摘要

Within any manufacturing environment, the selection of the production or assembly machines is part of the day to day responsibilities of management. This is especially true when there are multiple types of machines that can be used to perform each assembly or manufacturing process. As a result, it is critical to find the optimal way to select machines when there are multiple related assembly machines available. The objective of this research is to develop and present a model that can provide guidance to management when making machine selection decisions of parallel, non-identical, related electronics assembly machines. A model driven Decision Support System (DSS) is used to solve the problem with the emphasis in optimizing available resources, minimizing production disruption, thus minimizing cost. The variables that affect electronics product costs are considered in detail. The first part of the Decision Support System was developed using Microsoft Excel as an interactive tool. The second part was developed through mathematical modeling with AMPL9 mathematical programming language and the solver CPLEX90 as the optimization tools. The mathematical model minimizes total cost of all products using a similar logic as the shortest processing time (SPT) scheduling rule. This model balances machine workload up to an allowed imbalance factor. The model also considers the impact on the product cost when expediting production. Different scenarios were studied during the sensitivity analysis, including varying the amount of assembled products, the quantity of machines at each assembly process, the imbalance factor, and the coefficient of variation (CV) of the assembly processes. The results show that the higher the CV, the total cost of all products assembled increased due to the complexity of balancing machine workload for a large number of products. Also, when the number of machines increased, given a constant number of products, the total cost of all products assembled increased because it is more difficult to keep the machines balanced. Similar results were obtained when a tighter imbalance factor was used.
机译:在任何制造环境中,选择生产或组装机器都是日常管理的一部分。当有多种类型的机器可用于执行每个组装或制造过程时,尤其如此。因此,当有多个可用的相关组装机器时,找到选择机器的最佳方法至关重要。这项研究的目的是开发并提出一个模型,该模型可以在做出并行,不相同的相关电子装配机器的​​机器选择决策时为管理提供指导。模型驱动的决策支持系统(DSS)用于解决问题,重点在于优化可用资源,最大程度地减少生产中断,从而最大程度地降低成本。将详细考虑影响电子产品成本的变量。决策支持系统的第一部分是使用Microsoft Excel作为交互式工具开发的。第二部分是通过使用AMPL9数学编程语言和求解器CPLEX90作为优化工具的数学建模开发的。该数学模型使用与最短处理时间(SPT)调度规则类似的逻辑,将所有产品的总成本降至最低。该模型将机器工作负载平衡到允许的不平衡因素。该模型还考虑了加快生产时对产品成本的影响。在敏感性分析过程中研究了不同的场景,包括改变组装产品的数量,每个组装过程中的机器数量,不平衡因子以及组装过程的变异系数(CV)。结果表明,CV越高,由于平衡大量产品的机器工作负载的复杂性,所有组装产品的总成本增加了。同样,当机器数量增加时,给定恒定数量的产品,所有组装产品的总成本也会增加,因为保持机器平衡更加困难。当使用更严格的失衡因子时,可获得类似的结果。

著录项

  • 作者

    Mendez Pinero Mayra I.;

  • 作者单位
  • 年度 2010
  • 总页数
  • 原文格式 PDF
  • 正文语种 en_US
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