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An integrated fuzzy DEA-Fuzzy simulation approach for optimization of operator allocation with learning effects in multi products CMS

机译:集成模糊DEA-Fuzzy仿真方法,可在多产品CMS中优化具有学习效果的操作员分配

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摘要

This paper presents an integrated fuzzy data envelopment analysis (FDEA) and fuzzy computer simulation approach for optimization of operator allocation in multi product cellular manufacturing systems (CMS) with learning effects. Operator allocation with learning effects is a challenging issue in flexible manufacturing systems in general and in CMS in particular. The main contribution of this work is taking into consideration various operators layouts and learning effects using fuzzy simulation and fuzzy DEA. FDEA is utilized to assess simulation alternatives in various levels of uncertainty. Previous studies consider only one type of product with crisp inputs, whereas this study considers multi-products and fuzzy set up times and processing times for CMS modeling. In addition, this study considers and integrates learning effects for optimum operators' allocation. Moreover, more robust CMS assessment indicators are used in the proposed model. A case study illustrates the practicability, effectiveness and superiority of the proposed methodology.
机译:本文提出了一种集成的模糊数据包络分析(FDEA)和模糊计算机仿真方法,用于在具有学习效果的多产品细胞制造系统(CMS)中优化操作员分配。总体而言,具有学习效果的操作员分配在柔性制造系统中尤其是CMS中是一个具有挑战性的问题。这项工作的主要贡献是考虑了使用模糊模拟和模糊DEA的各种操作员布局和学习效果。 FDEA用于评估各种不确定性水平下的仿真替代方案。先前的研究仅考虑一种具有清晰输入的产品,而本研究则考虑了多种产品以及CMS建模的模糊设置时间和处理时间。此外,本研究考虑并整合了学习效果,以优化操作员的分配。此外,在该模型中使用了更强大的CMS评估指标。案例研究说明了所提出方法的实用性,有效性和优越性。

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