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A Simulation Analysis of Factors Influencing the Attractiveness of Group Technology Cellular Layouts

Author

Listed:
  • John S. Morris

    (College of Business and Economics, University of Idaho, Moscow, Idaho 83843)

  • Richard J. Tersine

    (College of Business Administration, University of Oklahoma, Norman, Oklahoma 73019)

Abstract

Group Technology (GT) is a multi-faceted approach to batch production that includes the reconfiguration of plant equipment from a functional layout to a series of product-oriented layouts that are referred to as manufacturing cells. The cells are dedicated to process families of parts that have similar machine operations. The purported benefits of GT over traditional functional layouts range from reduced work-in-process inventory and throughput times to increased worker satisfaction and productivity. However, recent simulation studies challenge some of these claims of superior performance for cellular layouts. This research examines the influence that factors in a firm's operating environment have on the performance of cellular layouts. A simulation model using hypothetical shop data is used to compare a process layout to a cellular layout using mean throughput time and mean level of work-in-process inventory as performance measures. The operating variables analyzed are (1) the ratio of setup to process time, (2) transfer time of material between work centers, (3) demand stability, and (4) the flow of work within cells. None of the individual changes in levels of operating variables produced a clear advantage for cellular layouts. However, the results from these experiments were used to postulate an "ideal" environment for cellular layouts. This environment is characterized as having a high ratio of setup to process time, stable demand, unidirectional flow of work within a cell, and a substantial level of material movement times between process departments. When all of these conditions are present, the cellular layout outperforms the process layout on both performance measures.

Suggested Citation

  • John S. Morris & Richard J. Tersine, 1990. "A Simulation Analysis of Factors Influencing the Attractiveness of Group Technology Cellular Layouts," Management Science, INFORMS, vol. 36(12), pages 1567-1578, December.
  • Handle: RePEc:inm:ormnsc:v:36:y:1990:i:12:p:1567-1578
    DOI: 10.1287/mnsc.36.12.1567
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    Citations

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    Cited by:

    1. Benjaafar, Saifallah, 1996. "Modeling and analysis of machine sharing in manufacturing systems," European Journal of Operational Research, Elsevier, vol. 91(1), pages 56-73, May.
    2. Balakrishnan, Jaydeep & Cheng, Chun Hung, 2007. "Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions," European Journal of Operational Research, Elsevier, vol. 177(1), pages 281-309, February.
    3. Shambu, Girish & Suresh, Nallan C., 2000. "Performance of hybrid cellular manufacturing systems: A computer simulation investigation," European Journal of Operational Research, Elsevier, vol. 120(2), pages 436-458, January.
    4. Jensen, John B., 2000. "The impact of resource flexibility and staffing decisions on cellular and departmental shop performance," European Journal of Operational Research, Elsevier, vol. 127(2), pages 279-296, December.
    5. Albino, Vito & Claudio Garavelli, A., 1999. "Limited flexibility in cellular manufacturing systems: A simulation study," International Journal of Production Economics, Elsevier, vol. 60(1), pages 447-455, April.
    6. Kannan, Vijay R. & Palocsay, Susan W., 1999. "Cellular vs process layouts: an analytic investigation of the impact of learning on shop performance," Omega, Elsevier, vol. 27(5), pages 583-592, October.
    7. Shruti Shashikumar & Rakesh D. Raut & Vaibhav S. Narwane & Bhaskar B. Gardas & Balkrishna E. Narkhede & Anjali Awasthi, 2019. "A novel approach to determine the cell formation using heuristics approach," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 628-656, September.
    8. Lee, Shine-Der & Chiang, Chih-Ping, 2002. "Cell formations in the uni-directional loop material handling environment," European Journal of Operational Research, Elsevier, vol. 137(2), pages 401-420, March.
    9. Shafer, S. M. & Meredith, J. R. & Marsh, R. F., 1995. "A taxonomy for alternative equipment groupings in batch environments," Omega, Elsevier, vol. 23(4), pages 361-376, August.
    10. Hosseini, Amir & Otto, Alena & Pesch, Erwin, 2024. "Scheduling in manufacturing with transportation: Classification and solution techniques," European Journal of Operational Research, Elsevier, vol. 315(3), pages 821-843.
    11. D'Angelo, Andrea & Gastaldi, Massimo & Levialdi, Nathan, 2000. "Production variability and shop configuration: An experimental analysis," International Journal of Production Economics, Elsevier, vol. 68(1), pages 43-57, October.
    12. Al-Mubarak, Fahad & Canel, Cem & Khumawala, Basheer M., 2003. "A simulation study of focused cellular manufacturing as an alternative batch-processing layout," International Journal of Production Economics, Elsevier, vol. 83(2), pages 123-138, February.
    13. Agarwal, Atul, 2008. "Partitioning bottleneck work center for cellular manufacturing: An integrated performance and cost model," International Journal of Production Economics, Elsevier, vol. 111(2), pages 635-647, February.
    14. Jing, Hao & Sheng, Lijuan & Luo, Chaorui & Kwak, Choonjong, 2021. "Statistical analysis of family based dispatching rules and preemption," International Journal of Production Economics, Elsevier, vol. 240(C).
    15. Hassan, Mohsen M. D., 1995. "Layout design in group technology manufacturing," International Journal of Production Economics, Elsevier, vol. 38(2-3), pages 173-188, March.
    16. Garavelli, A. Claudio, 2001. "Performance analysis of a batch production system with limited flexibility," International Journal of Production Economics, Elsevier, vol. 69(1), pages 39-48, January.
    17. Shanker, Ravi & Vrat, Prem, 1998. "Post design modeling for cellular manufacturing system with cost uncertainty," International Journal of Production Economics, Elsevier, vol. 55(1), pages 97-109, June.
    18. Logendran, Rasaratnam & Talkington, Diane, 1997. "Analysis of cellular and functional manufacturing systems in the presence of machine breakdown," International Journal of Production Economics, Elsevier, vol. 53(3), pages 239-256, December.
    19. Chandrashekar, Ashok & Callarman, Thomas E., 1998. "A modelling study of the effects of continuous incremental improvement in the case of a process shop," European Journal of Operational Research, Elsevier, vol. 109(1), pages 111-121, August.
    20. Plaquin, Marie-France & Pierreval, Henri, 2000. "Cell formation using evolutionary algorithms with certain constraints," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 267-278, March.
    21. Tharanga Rajapakshe & Milind Dawande & Chelliah Sriskandarajah, 2011. "Quantifying the Impact of Layout on Productivity: An Analysis from Robotic-Cell Manufacturing," Operations Research, INFORMS, vol. 59(2), pages 440-454, April.
    22. Das, K. & Lashkari, R.S. & Sengupta, S., 2007. "Reliability consideration in the design and analysis of cellular manufacturing systems," International Journal of Production Economics, Elsevier, vol. 105(1), pages 243-262, January.
    23. Kannan, V. R. & Ghosh, S., 1995. "Using dynamic cellular manufacturing to simplify scheduling in cell based production systems," Omega, Elsevier, vol. 23(4), pages 443-452, August.

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