Authors: Ashutosh Gupta; Pramod K. Jain; Dinesh Kumar
Addresses: Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee – 247667, India ' Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee – 247667, India ' Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee – 247667, India
Abstract: The reconfigurable manufacturing systems (RMSs) is the next step in manufacturing, allowing the production of any quantity of highly customised 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 is 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 reconfigurability issues. The aim of this work is to establish a methodology for grouping parts into families for effective working of reconfigurable manufacturing systems (RMSs). The methodology carried out in two phases. In the first phase, the correlation matrix is used as similarity coefficient matrix to form the part operational similarity followed by agglomerative hierarchical K-means algorithm used for the parts family formation. In the second phase, cost model is developed to select and sequence the formed part families, resulting in a minimum cost solution to the problem.
Keywords: reconfigurable manufacturing systems; RMS; part family formation; part families; K-means clustering; similarity coefficient; correlation matrix; cost models; sequencing.
International Journal of Internet Manufacturing and Services, 2014 Vol.3 No.3, pp.244 - 262
Received: 13 Apr 2013
Accepted: 08 Jan 2014
Published online: 05 Jun 2014 *