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New bi-objective robust design-based utilisation towards dynamic cell formation problem with fuzzy random demands

机译:基于双目标鲁棒设计的新方法对带有模糊随机需求的动态细胞形成问题的利用

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摘要

Generally, one of the most important issues which cause a production system not to be an efficient one is unemployed capacities of both machines and workers. On the other hand, adaptive design's most exploiting facilities are not practical for any cases (huge machines). Hence, sometimes manufacturing firms are in need of robust design. In this paper, a robust design is considered to configure cells in a dynamic cellular manufacturing system to overcome the onerous machine relocation costs. Most of researches on robust design are trying to reduce the number of facilities while, here, this idea is adopted accompanying with practical concepts of facility utilisation with new mathematical formulae. Then, a multi-objective mathematical model containing the minimisation of the inter-cell movements besides maximising the machine and worker utilisation is developed. Some other supplements are the following: (1) considering a cubic space representation for calculation of inter-cell movements and (2) fuzzy random nature of part demands. Above all, a new goal programming method named 'percentage multi-choice goal programming' (PMCGP) is innovated to solve the proposed multi-objective model. Finally, a comprehensive numerical example is generated randomly to verify the proposed model.
机译:通常,导致生产系统效率不高的最重要问题之一是机器和工人的无用能力。另一方面,自适应设计的最大利用设施在任何情况下(大型机器)都不实用。因此,有时制造公司需要坚固的设计。在本文中,考虑了一种健壮的设计来配置动态蜂窝制造系统中的单元,以克服繁重的机器重新安置成本。健壮设计的大多数研究都在试图减少设施的数量,而在此,这一想法与设施利用的实用概念一起采用了新的数学公式。然后,建立了一个多目标数学模型,该模型除了使机器和工人的利用率最大化外,还包含最小化单元间运动的功能。其他一些补充如下:(1)考虑三次空间表示以计算小区间运动,以及(2)零件需求的模糊随机性。最重要的是,创新了一种称为“百分比多选目标规划”(PMCGP)的新目标规划方法,以解决所提出的多目标模型。最后,随机生成一个综合数值示例,以验证所提出的模型。

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