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Journal of Applied Mathematics
Volume 2013 (2013), Article ID 487694, 10 pages
http://dx.doi.org/10.1155/2013/487694
Research Article

An Integrated Model for Production Planning and Cell Formation in Cellular Manufacturing Systems

1Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Selangor, Selangor Darul Ehsan, Malaysia
2Department of Industrial Engineering, Islamic Azad University, Lenjan Branch, isfahan, Iran

Received 17 May 2012; Revised 10 November 2012; Accepted 15 November 2012

Academic Editor: Yuri Sotskov

Copyright © 2013 Reza Raminfar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Cellular manufacturing (CM) is a production approach directed towards reducing costs, as well as increasing system's flexibility in today's small-to-medium lot production environment. Many structural and operational issues should be considered for a successful CM design and implementation such as cell formation (CF), production planning, and facility layout. Most researchers have addressed these issues sequentially or independently, instead of jointly optimizing a combination of these issues. In order to attain better results to ensure that the system will be capable of remaining efficient in unknown future situations, these issues should be addressed simultaneously. In this paper, a mathematical model is developed using an integrated approach for production planning and cell formation problems in a CM. A set of numerical examples are provided from existing the literature in order to test and illustrate the proposed model. In order to evaluate and verify the performance of the proposed model, it is compared with a well-known cell formation methods (rank order clustering and direct clustering analysis), using group capability index (GCI) measure. The results and comparisons indicate that the proposed model has a significantly higher and satisfactory performance and it is reliable for the design and the analysis of CM systems.