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,...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.展开更多
文摘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.
