Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection

Sihan Huang*, Yan Yan

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

22 引用 (Scopus)

摘要

To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types.

源语言英语
页(从-至)4471-4488
页数18
期刊International Journal of Production Research
58
14
DOI
出版状态已出版 - 17 7月 2020

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Huang, S., & Yan, Y. (2020). Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection. International Journal of Production Research, 58(14), 4471-4488. https://doi.org/10.1080/00207543.2019.1654631