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A new cellular manufacturing layout: Multi-floor linear cellular manufacturing layout

机译:一种新的蜂窝制造布局:多层线性蜂窝制造布局

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The article puts forward the new layout methodology of the multi-floor linear cellular manufacturing layout. The proposed equipment layout methodology not just breaks the conventional single-floor linear cellular manufacturing layout but also meets the layout requirements of the intelligent manufacturing workshop for the stereoscopic aisle manufacturing cell. The layout methodology takes into account the least space occupation as well as the shortest total distance of logistics as the objective function, besides considering the limitations that exist between the equipment, different planes, different levels, and so on; also, a mathematical model is put forward. The multi-floor linear cellular manufacturing layout is solved based on the self-adapting multi-objective fruit fly optimization algorithm that refers to an algorithm combining fruit fly optimization algorithm and NSGA-II. Self-adapting multi-objective fruit fly optimization algorithm makes use of the fast nondominated sorting for the multi-target food concentration calculation, together with designing the adaptive olfactory search and visual search, and employing the perturbation operations for flight strategies, aimed at ensuring the population diversity. Simulation cases suggest that self-adapting multi-objective fruit fly optimization algorithm has stronger advantages as compared with multi-objective fruit fly algorithm and elitist non-dominated sorting genetic algorithm (NSGA-II) in the solution of multi-floor linear cellular manufacturing layout problems. The final engineering case application sheds light on the fact that multi-floor linear cellular manufacturing layout saves 57.6% of the area, in addition to 23.7% of space, and 29.2% of the handling distance as compared with single-floor linear cellular manufacturing layout. Accordingly, multi-floor linear cellular manufacturing layout has a specific reference value in the layout of facilities in the intelligent manufacturing plants.
机译:该文章提出了多层线性蜂窝制造布局的新布局方法。所提出的设备布局方法不仅破坏了传统的单层线性蜂窝制造布局,而且还满足立体过道制造单元的智能制造车间的布局要求。除了考虑设备,不同的平面,不同级别等的限制,布局方法还考虑了最小空间占用以及物流的最短总距离;此外,提出了一种数学模型。基于自适度的多目标果蝇优化算法来解决多层线性蜂窝制造布局,其是指结合果蝇优化算法和NSGA-II的算法。自适应多目标果蝇优化算法利用快速的非目标食物浓度计算,以及设计自适应嗅探和视觉搜索,并采用飞行策略的扰动操作,旨在确保人口多样性。模拟案例表明,与多目标果蝇算法和求电子非主导分类遗传算法(NSGA-II)相比,自适应多目标果蝇优化算法具有较强的优势,在多层线性蜂窝制造布局的解决方案中问题。最终的工程案例申请揭示了多层线性蜂窝制造布局,除了23.7%的空间的23.7%,与单层线性蜂窝制造布局相比,23.7%,占搬运距离的29.2% 。因此,多层线性蜂窝制造布局在智能制造工厂的设施布局中具有特定的参考值。

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