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Similarity Coefficient of RMS Part Family Grouping Considering Reconfiguration Efforts
Author(s) -
Sihan Huang,
Guoxin Wang,
Yan Yan,
Jia Hao
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2882179
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
A reconfigurable manufacturing system (RMS) built around a part family is a paradigm to meet dynamic demands and can provide the exact functionality and capacity of the associated part family. The reconfiguration of an RMS is a complex process, given the practical situation of the RMS structure. Furthermore, the reconfiguration complexity of an RMS determines the success of RMS implementation. The reconfiguration complexity can be evaluated using reconfiguration efforts. Eliminating parts involves more reconfiguration efforts compared to complete reconfiguration from a part family and will decrease the reconfiguration complexity of RMS implementation based on the corresponding part family. Therefore, a similarity coefficient that considers the reconfiguration efforts of RMS part family grouping is proposed in this paper. First, the definition of reconfiguration efforts is given based on the system configurations of each part, including actions such as function add, function delete, function swap, and function replace. Second, the common operation sequence (COS) and the longest common subsequence (LCS) between parts are analyzed. Third, the similarity between parts is calculated based on the reconfiguration efforts, the COS, and the LCS. The average linkage clustering algorithm is adopted for grouping the parts into families based on similarity. Finally, a case study is presented to implement the proposed part family grouping method and validate its effectiveness.

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