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Machine Cell Formation with Sequence Data for Cellular and Automated Manufacturing Systems

机译:机器电池形成,具有用于蜂窝和自动化制造系统的序列数据

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Production sequence and product volumes, if incorporated properly in determining the machine cells in the cellular and automated manufacturing systems, can enhance the quality of solutions and reduce the number of intercellular moves and material handling cost. Thus, the number of trips between a pair of machines from a part type should be incorporated in the determination of similarity for respective pairs of machines. Measures for cell formation based on operations sequence utilizing ordinal data are few and have many limitations. Also they count the number of the trips for each individual part instead of counting the weights of the batches. A new similarity measure based on the sequence of operations parameter and the batch size of the parts are introduced. The new similarity measure showed more sensitivity to the intercellular moves and better machine grouping.
机译:生产顺序和产品体积,如果在确定蜂窝和自动化制造系统中的机器电池时掺入,可以提高解决方案的质量,并减少细胞间移动的数量和材料处理成本。因此,应当结合来自部件类型的一对机器之间的跳频的数量在确定各对机器的相似性中。基于使用序数数据的操作序列的细胞形成措施很少,并且有很多限制。此外,它们计算每个单独部分的跳频的数量,而不是计算批次的权重。介绍了基于操作参数序列和零件的批量大小的新的相似性度量。新的相似性措施对细胞间移动和更好的机器分组表示更敏感。

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