A novel approach for part family formation using K-means algorithm

作     者：Ashutosh Gupta P.K.Jain Dinesh Kumar 

作者机构：Department of Mechanical and Industrial EngineeringIndian Institute of Technology Roorkee 

出 版 物：《Advances in Manufacturing》 (先进制造进展（英文版）)

年 卷 期：2013年第1卷第3期

页      面：241-250页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0807[工学-动力工程及工程热物理] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 

主　　题：Reconfigurable manufacturing system (RMS)Part family formation K means algorithm Similaritycoefficient Correlation matrix 

摘      要：The reconfigurable manufacturing system （RMS） is the next step in manufacturing, allowing the production of any quantity of highly customized and complex parts together with the benefits of mass production. In RMSs, parts are grouped into families, each of which requires a specific system configuration. Initially system is configured to produce the first family of parts. Once it is finished, the system will be reconfigured in order to produce the second family, and so forth. The effectiveness of a RMS depends on the formation of the optimum set of part families addressing various recon figurability issues. The aim of this work is to establish a methodology for grouping parts into families for effective working of RMS. The methodology carried out in two phases. In the first phase, the correlation matrix is used as similarity coefficient matrix. In the second phase, agglomerative hier archical Kmeans algorithm is used for the parts family for mation resulting in an optimum set of part families for reconfigurable manufacturing system.