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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/10815
Title: A novel approach for part family formation for reconfiguration manufacturing system
Authors: Gupta A.
Jain, P. K.
Kumar D.
Published in: OPSEARCH
Abstract: The Reconfigurable Manufacturing Systems (RMS) 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. For this, a two-phase approach is developed where parts are first grouped into families and then families are sequenced, computing the required machines and modules configuration for each family. In the First phase, parts are grouped into families based on their common features. The correlation matrix is developed as operations sequence similarity coefficient matrix. Principal Component Analysis (PCA) is applied to find the eigenvalues and eigenvectors on the correlation similarity matrix. A scatter plot analysis as a cluster analysis is applied to make parts groups while maximizing correlation between parts as per operations sequence similarity. Agglomerative Hierarchical K-means algorithm improved the parts family formation using Euclidean distance resulting a set of part families. In the second phase, optimal selection and sequences of the resulted part families is achieved by using a Mixed Integer Linear Programming (MILP) model minimizing reconfigurability and under-utilization costs to get the minimum cost solution. © 2013 Operational Research Society of India.
Citation: OPSEARCH (2014), 51(1): 76-97
URI: https://doi.org/10.1007/s12597-013-0133-6
http://repository.iitr.ac.in/handle/123456789/10815
Issue Date: 2014
Publisher: Springer India
Keywords: Cluster analysis
K-means algorithm
MILP
Part family selection
Principle Component Analysis
Reconfigurable manufacturing system
Sequencing
ISSN: 303887
Author Scopus IDs: 57198676757
7402520507
57202478211
Author Affiliations: Gupta, A., Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, India
Jain, P.K., Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, India
Kumar, D., Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, India
Corresponding Author: Gupta, A.; Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, India; email: ashuaec72@gmail.com
Appears in Collections:Journal Publications [ME]

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