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Machine cell formation for production management in cellular manufacturing systems

机译:机器单元形成,用于蜂窝制造系统中的生产管理

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摘要

The formation of machine-part families is an important task in the design of cellular manufacturing systems. Manufacturing cell grouping has the effect of reducing material handing cost and work in process. Among the many methods utilized in machine cells formation, the similarity coefficient method is most widely used. Production sequence and product volumes, if incorporated properly in determining the machine cells, can enhance the quality of solutions and reduce the number of intercellular movements. Measures for cell formation based on operations sequence utilizing ordinal production data are few and have many limitations, such as counting the number of the trips for each individual part instead of counting the weights of the batches. A new ordinal production data similarity coefficient based on the sequence of operations and the batch size of the parts is introduced. Furthermore, a new clustering algorithm for machine cell formation is proposed. The new similarity measure showed more sensitivity to the intercellular movements and the clustering algorithm showed better machine grouping.
机译:机器零件族的形成是蜂窝制造系统设计中的重要任务。制造单元分组具有降低材料处理成本和过程中工作的效果。在机器单元形成中使用的许多方法中,相似系数方法是使用最广泛的方法。如果在确定机器单元中正确地结合了生产顺序和产品量,则可以提高溶液的质量并减少细胞间运动的次数。基于利用有序生产数据的操作顺序进行细胞形成的措施很少,并且有很多局限性,例如计算每个单独零件的行程次数,而不是计算批次的重量。介绍了一种基于操作顺序和零件批量大小的新序数数据相似系数。此外,提出了一种新的机器单元形成聚类算法。新的相似性度量显示出对细胞间运动的更高敏感性,并且聚类算法显示出更好的机器分组。

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