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Formation of machine groups and part families in cellular manufacturing systems using a correlation analysis approach


  • Hachicha, Wafik
  • Masmoudi, Faouzi
  • Haddar, Mohamed


The important step in the design of a cellular manufacturing (CM) system is to identify the part families and machine groups and consequently to form manufacturing cells. The scope of this article is to formulate a multivariate approach based on a correlation analysis for solving cell formation problem. The proposed approach is carried out in three phases. In the first phase, the correlation matrix is used as similarity coefficient matrix. In the second phase, 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 simultaneously machine groups and part families while maximizing correlation between elements. In the third stage, an algorithm is improved to assign exceptional machines and exceptional parts using respectively angle measure and Euclidian distance. The proposed approach is also applied to the general Group Technology (GT) problem in which exceptional machines and part are considered. Furthermore, the proposed approach has the flexibility to consider the number of cells as a dependent or independent variable. Two numerical examples for the design of cell structures are provided in order to illustrate the three phases of proposed approach. The results of a comparative study based on multiple performance criteria show that the present approach is very effective, efficient and practical.

Suggested Citation

  • Hachicha, Wafik & Masmoudi, Faouzi & Haddar, Mohamed, 2006. "Formation of machine groups and part families in cellular manufacturing systems using a correlation analysis approach," MPRA Paper 3975, University Library of Munich, Germany, revised 04 Jan 2007.
  • Handle: RePEc:pra:mprapa:3975

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    References listed on IDEAS

    1. J. E. King, 1999. "Introduction," Review of Political Economy, Taylor & Francis Journals, vol. 11(3), pages 251-255.
    2. Kitaoka, Masatoshi & Nakamura, Rui & Serizawa, Seiichi & Usuki, Jun, 1999. "Multivariate analysis model for machine-part cell formation problem in group technology," International Journal of Production Economics, Elsevier, vol. 60(1), pages 433-438, April.
    3. Yin, Yong & Yasuda, Kazuhiko, 2006. "Similarity coefficient methods applied to the cell formation problem: A taxonomy and review," International Journal of Production Economics, Elsevier, vol. 101(2), pages 329-352, June.
    4. Stawowy, Adam, 2006. "Evolutionary strategy for manufacturing cell design," Omega, Elsevier, vol. 34(1), pages 1-18, January.
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    Cited by:

    1. Hachicha, Wafik & Masmoudi, Faouzi & Haddar, Mohamed, 2008. "A Taguchi method application for the part routing selection in Generalized Group Technology: A case Study," MPRA Paper 12376, University Library of Munich, Germany.
    2. Faouzi Masmoudi & Wafik Hachicha & Mohamed Haddar, 2008. "A New Combined Framework for the Cellular Manufacturing Systems Design," Post-Print halshs-00325336, HAL.
    3. Hachicha, Wafik & Masmoudi, Faouzi & Haddar, Mohamed, 2007. "An improvement of a cellular manufacturing system design using simulation analysis," MPRA Paper 8922, University Library of Munich, Germany, revised 22 Dec 2007.

    More about this item


    cellular manufacturing; cell formation; correlation matrix; Principal Component Analysis; exceptional machines and parts;

    JEL classification:

    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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