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A fuzzy multiple objective programming approach for the selection of a flexible manufacturing system

机译:选择柔性制造系统的模糊多目标规划方法

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摘要

Global competition in manufacturing environment has forced the firms to consider increasing the quality and responsiveness to customization, while decreasing costs. The evolution of flexible manufacturing systems offers great potential for increasing flexibility and changing the basis of competition by ensuring both cost effective and customized manufacturing at the same time. This paper presents a fuzzy multiple objective programming approach to facilitate decision making in the selection of a flexible manufacturing system (FMS). Fuzzy set theory is introduced in the model to incorporate the vague nature of future investments and the uncertainty of the production environment. Linguistic variables and triangular fuzzy numbers are used to quantify the vagueness inherent in decision parameters, e.g., increase in market response, improvement in quality, reduction in setup cost, and so forth. The model proposed in this paper determines the most appropriate FMS alternative through maximization of objectives such as reduction in labor cost, reduction in setup cost, reduction in work-in-process (WIP), increase in market response and improvement in quality, and minimization of capital and maintenance cost and floor space used. These objectives are assigned priorities indicating their importance levels using linguistic variables. A numerical example is presented to illustrate the application of the model developed in this paper.
机译:全球制造环境的竞争迫使公司不得不考虑提高质量和对定制的响应能力,同时降低成本。柔性制造系统的发展为确保灵活性和定制制造同时提供了巨大的潜力,可以提高灵活性并改变竞争基础。本文提出了一种模糊的多目标规划方法,以帮助选择柔性制造系统(FMS)时进行决策。在模型中引入了模糊集理论,以结合未来投资的模糊性质和生产环境的不确定性。语言变量和三角模糊数用于量化决策参数固有的模糊性,例如,市场响应的增加,质量的提高,安装成本的降低等。本文提出的模型通过最大化目标来确定最合适的FMS替代方案,例如降低劳动力成本,降低安装成本,减少在制品(WIP),提高市场响应能力和质量以及最小化目标。资金和维护成本以及所用的占地面积。使用语言变量为这些目标分配优先级,指示其重要性级别。数值例子说明了本文开发的模型的应用。

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