Abstract
In recent years cellular manufacturing has become an effective tool for improving productivity. Attainment of full benefits of cellular manufacturing depends firstly on the design of the machine cells and part families and secondly on the method of operation which take full advantages of cell properties. Inappropriate methods of loading and scheduling can even lead to the failure of cellular manufacturing systems (CMS), however efficiently the cell is designed. This paper examines three array-based clustering algorithms, namely rank order clustering (ROC), rank order clustering-2 (ROC2) and direct clustering analysis (DCA) for manufacturing cell formation, with a real-life example to demonstrate the effectiveness of various clustering algorithms. The machine cell formation methods considered in this comparative and evaluative study belongs to the cluster formation approach of solving the MCF problem. The most effective method is selected and used to build the cellular manufacturing system. The comparison and evaluation are performed using four published performance measures and compares the improvements with the existing conventional system and the cellular manufacturing system. The above algorithms were written in the C++ language on an Intel/Pentium III-PC-compatible system.
Similar content being viewed by others
References
Akturk MS, Turkcan A (2000) Cellular manufacturing system design using a holonistic approach. Int J Prod Res 38(10):2327–2347
Anderberg MR (1973) Cluster analysis for applications. Academic Press, New York
Burbridge JL (1971) Production flow analysis. Prod Eng 50:139–152
Ballakur A, Steudel HJ (1987) A within-cell utilization based heuristic for designing cellular manufacturing systems. Int J Prod Res 25:639–665
Carrie AS (1973) Numerical taxonomy applied to group technology and plant layout. Int J Prod Res 11:399–416
Chan FTS, Abhary K (1996) Design and evaluation of automated cellular manufacturing systems with simulation modelling and AHP approach: a case study. Int J Manuf Technol Manag, Integr Manuf Syst 7(6):39
Chan HM, Milner DA (1982) Direct clustering algorithm for group formation in cellular manufacture. J Manuf Syst 1:65–75
Chan FTS, Lau KW, Chan PLY (2004) A holistic approach to manufacturing cell formation: incorporation of machine flexibility and machine aggregation. Proc Inst Mech Eng B J Eng Manuf 218(10):1279–1296
Chan FTS, Lau KW, Chan PLY, Choy KL (2006) Two-stage approach for machine-part grouping and cell layout problems. Int J Rob Comput Integr Manuf 22(3):217–238
Chandrasekharan MP, Rajagopalan R (1986a) An ideal seed non-hierarchical clustering algorithm for cellular manufacturing. Int J Prod Res 24:451–464
Chandrasekharan MP, Rajagopalan R (1986b) MODROC: an extension of rank order clustering for group technology. Int J Prod Res 24:1221–1233
Cheng CH, Kumar A, Motwani J (1995) A comparative examination of selected cellular manufacturing clustering algorithms. Int J Oper Prod Manage 15(12):86–97
Chu CH (1989) Clustering analysis in manufacturing cellular formation. OMEGA: Int J Manag Sci 17:289–295
Chu CH, Tsai M (1990) A comparison of three array-based clustering techniques for manufacturing cell formation. Int J Prod Res 28(8):1417–1433
Cunningham KM, Ogilvie JC (1971) Evaluation of hierarchical grouping techniques: a preliminary study. Comput J 15:209–213
Dimopoulos C, Mort N (2001) A hierarchical clustering methodology based on genetic programming for the solution of simple cell-formation problems. Int J Prod Res 39(1):185–198
Gongaware TA, Ham I (1981) Cluster analysis applications for group technology-manufacturing systems. Manuf Eng Trans 503–508
Harhalakis G, Nagi R, Proth JM (1990) An efficient heuristic in manufacturing cell formation for group technology applications. Int J Prod Res 28(1):185–198
Hassan M, Selim, Reda MS, Abdel AAL, Aby I, Mahdi (2003) Formation of machine groups and part families: a modified SLC method and comparative study. J Integr Manuf Syst 123–137
Hsu CP (1990) Similarity coefficient approaches to machine-component cell formation in cellular manufacturing: a comparative study. PhD thesis, Industrial and Systems Engineering, University of Wisconsin-Milwaukee
Jacobs FR (1985) Computerized production flow analysis. In: Whitehouse GE (ed) Soft cover software: 28 microcomputer programs for IEs and manager. IE and Management Press, Georgia, pp 61–67
Kaparthi S, Suresh NC (1994) Performance of selected part-machine grouping techniques for data sets of wide ranging sizes and imperfection. Decis Sci 25(4):515–539
Khator SK, Irani SA (1987) Cell formation in group technology: a new approach. Comput Ind Eng 12:131–142
King JR (1980a) Machine-component group formation in-group technology. OMEGA 8:193–199
King JR (1980b) Machine-component grouping in production flow analysis: an approach using a rank order-clustering algorithm. Int J Prod Res 18:213–232
King JR, Nakornchai V (1982) Machine-component group formation in-group technology: review and extension. Int J Prod Res 20:117–133
Kuiper FK, Fisher L (1975) A Monte Carlo comparison of six clustering procedures. Biometrics 777–783
Kusiak A (1987) The generalized group technology concept. Int J Prod Res 25:561–569
Kusiak A, Chow WS (1987) Efficient solving of the group technology problem. J Manuf Syst 6:117–124
Mansouri SA, Moattar-Husseini SM, Zegordi SH (2003) A genetic algorithm for multiple objective dealing with exceptional elements in cellular manufacturing. Prod Plan Control 14(5):437–446
McAuley J (1972) Machine grouping for efficient production. Prod Eng 53–57
McCormick JR, WT, Scmwitzer PJ, White TW (1972) Problem decomposition and data reorganization by a clustering technique. Oper Res 20:993–1009
Miltenburg J, Zhang W (1991) A comparative evaluation of nine well-known algorithms for solving the cell formation problem in group technology. J Oper Manag 10:44–72
Mosier CT, Taube L (1985) Weighted similarity coefficient heuristics for the group technology machine clustering problem. Int J Manag Sci 13(6):577–583
Mosier CT (1989) An experiment investigating the application of clustering procedures and similarity coefficients to the GT machine cell formation problem. Int J Prod Res 27:1811–1835
Nair GJ, Narendran TT (1996) Grouping index: a new quantitative criterion for goodness of block-diagonal forms in-group technology. Int J Prod Res 34:2767–2782
Purcheck GFK (1974) Combinatorial groupings lattice-theoretical method for the design of manufacturing systems. J Cybern 4:27–60
Purcheck GFK (1975) A mathematical classification as a basis for the design of group technology production cells. Prod Eng 35–48
Rajagopalan R, Batra JL (1975) Design of cellular production systems: a graph theoretic approach. Int J Prod Res 13:567–579
Rand WM (1977) Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66:846–850
Sarker BR, Mondal S (1999) Grouping efficiency measures in cellular manufacturing: a survey and critical review. Int J Prod Res 37:285–314
Sarker BP, Khan MA (2001) Comparison of existing grouping efficiency measures and a new weighted efficiency measure. IIE Trans 33:11–27
Seifoddini H, Djassemi M (1996) A new grouping measure for evaluation of machine-component matrices. Int J Prod Res 34:1179–1193
Stanfel LE (1985) Machine clustering for economic production. Eng Costs Prod Econ 9:73–81
Tarsuslugil M, Bloor J (1979) The use of similarity coefficients and cluster analysis in production flow analysis. Proceedings of the 20th International Machine Tool Design and Research Conference, pp 525–531
Waghodekar PH, Sahu S (1984) Machine-component cell formation in-group technology: MACE. Int J Prod Res 22:937–948
Wemmerlov U (1984) Comments on direct clustering algorithm for group formation in cellular manufacture. J Manuf Syst 3
Wemmerlov U, Hyer NL (1986) Procedures for the part family/machine group identification problem in cellular manufacturing. J Oper Manag 6:125–147
Wemmerlov U, Hyer NL (1987) Research issues in cellular manufacturing. Int J Prod Res 25:413–431
Yasuda K, Yin Y (2001) A dissimilarity measure for solving the cell formation problem in cellular manufacturing. Int J Comput Ind Eng 39(1):1–17
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Murugan, M., Selladurai, V. Optimization and implementation of cellular manufacturing system in a pump industry using three cell formation algorithms. Int J Adv Manuf Technol 35, 135–149 (2007). https://doi.org/10.1007/s00170-006-0710-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-006-0710-4