Mathematical Problems in Engineering

Mathematical Problems in Engineering / 2007 / Article

Research Article | Open Access

Volume 2007 |Article ID 057128 | https://doi.org/10.1155/2007/57128

Jingshan Li, Ningjian Huang, "Quality Evaluation in Flexible Manufacturing Systems: A Markovian Approach", Mathematical Problems in Engineering, vol. 2007, Article ID 057128, 24 pages, 2007. https://doi.org/10.1155/2007/57128

Quality Evaluation in Flexible Manufacturing Systems: A Markovian Approach

Academic Editor: P. T. Kabamba
Received16 Mar 2007
Accepted09 May 2007
Published13 Jun 2007

Abstract

The flexible manufacturing system (FMS) has attracted substantial amount of research effort during the last twenty years. Most of the studies address the issues of flexibility, productivity, cost, and so forth. The impact of flexible lines on product quality is less studied. This paper intends to address this issue by applying a Markov model to evaluate quality performance of a flexible manufacturing system. Closed expressions to calculate good part probability are derived and discussions to maintain high product quality are carried out. An example of flexible fixture in machining system is provided to illustrate the applicability of the method. The results of this study suggest a possible approach to investigate the impact of flexibility on product quality and, finally, with extensions and enrichment of the model, may lead to provide production engineers and managers a better understanding of the quality implications and to summarize some general guidelines of operation management in flexible manufacturing systems.

References

  1. R. R. Inman, D. E. Blumenfeld, N. Huang, and J. Li, “Designing production systems for quality: research opportunities from an automotive industry perspective,” International Journal of Production Research, vol. 41, no. 9, pp. 1953–1971, 2003. View at: Publisher Site | Google Scholar
  2. D. E. Zoia, “Harbour Outlines Who's Winning and Why,” September 2005, http://WardsAuto.com/. View at: Google Scholar
  3. J. Payne and V. Cariapa, “A fixture repeatability and reproducibility measure to predict the quality of machined parts,” International Journal of Production Research, vol. 38, no. 18, pp. 4763–4781, 2000. View at: Publisher Site | Google Scholar | Zentralblatt MATH
  4. Z. M. Bi and W. J. Zhang, “Flexible fixture design and automation: review, issues and future directions,” International Journal of Production Research, vol. 39, no. 13, pp. 2867–2894, 2001. View at: Publisher Site | Google Scholar
  5. A. Bolat and C. Yano, “Procedures to analyze the tradeoffs between costs of setup and utility work for automobile assembly lines,” Tech. Rep. 89-3, Department of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, Mich, USA, 1989. View at: Google Scholar
  6. “Sector Notebook—Profile of the Fabricated Metal Products Industry—Part 2,” December 2005, http://www.epa.gov/compliance/resources/publications/assistance/sectors/notebooks/fabmetsnpt2.pdf. View at: Google Scholar
  7. “Automobile Production at OPEL, Bochum (Gemany),” http://www.profibus.com/pall/applications/casestudies/article/3043/. View at: Google Scholar
  8. D. A. Jacobs and S. M. Meerkov, “Asymptotically reliable serial production lines with a quality control system,” Computers & Mathematics with Applications, vol. 21, no. 11-12, pp. 85–90, 1991. View at: Publisher Site | Google Scholar | Zentralblatt MATH
  9. A. A. Bulgak, “Impact of quality improvement on optimal buffer designs and productivity in automatic assembly systems,” Journal of Manufacturing Systems, vol. 11, pp. 124–136, 1992. View at: Google Scholar
  10. M. Khouja, G. Rabinowitz, and A. Mehrez, “Optimal robot operation and selection using quality and output trade-off,” International Journal of Advanced Manufacturing Technology, vol. 10, no. 5, pp. 342–355, 1995. View at: Publisher Site | Google Scholar
  11. N. Viswanadham, S. M. Sharma, and M. Taneja, “Inspection allocation in manufacturing systems using stochastic search techniques,” IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans., vol. 26, no. 2, pp. 222–230, 1996. View at: Publisher Site | Google Scholar
  12. T. L. Urban, “Analysis of production systems when run length influences product quality,” International Journal of Production Research, vol. 36, no. 11, pp. 3085–3094, 1998. View at: Publisher Site | Google Scholar | Zentralblatt MATH
  13. C. H. Cheng, J. Miltenburg, and J. Motwani, “The effect of straight- and U-shaped lines on quality,” IEEE Transactions on Engineering Management, vol. 47, no. 3, pp. 321–334, 2000. View at: Publisher Site | Google Scholar
  14. S. A. I. Matanachai and C. A. Yano, “Balancing mixed-model assembly lines to reduce work overload,” IIE Transactions, vol. 33, no. 1, pp. 29–42, 2001. View at: Publisher Site | Google Scholar
  15. Y. Ding, J. Jin, D. Ceglarek, and J. Shi, “Process-oriented tolerancing for multi-station assembly systems,” IIE Transactions, vol. 37, no. 6, pp. 493–508, 2005. View at: Publisher Site | Google Scholar
  16. J. Li and D. E. Blumenfeld, “Quantitative analysis of a transfer production line with Andon,” IIE Transactions, vol. 38, no. 10, pp. 837–846, 2006. View at: Publisher Site | Google Scholar
  17. J. Li, D. E. Blumenfeld, and S. P. Marin, “Manufacturing system design to improve quality buy rate: an automotive paint shop application study,” IEEE Transactions on Automation Science and Engineering, vol. 4, no. 1, pp. 75–79, 2007. View at: Publisher Site | Google Scholar
  18. J. Li, D. E. Blumenfeld, and S. P. Marin, “Production system design for quality robustness: theory and application in automotive paint shops,” IIE Transactions, vol. 39, 2007. View at: Google Scholar
  19. J. Kim and S. B. Gershwin, “Integrated quality and quantity modeling of a production line,” OR Spectrum, vol. 27, no. 2-3, pp. 287–314, 2005. View at: Publisher Site | Google Scholar | MathSciNet
  20. N. Viswanadham and Y. Narahari, Performance Modeling of Automated Manufacturing System, Prentice-Hall, Englewood Cliffs, NJ, USA, 1992. View at: Google Scholar
  21. J. A. Buzacott and J. G. Shantikumar, Stochastic Models of Manufacturing Systems, Prentice-Hall, Englewood Cliffs, NJ, USA, 1993. View at: Google Scholar | Zentralblatt MATH
  22. H. Tempelmeier and H. Kuhn, Flexible Manufacturing Systems: Decision Support for Design and Operation, John Wiley & Sons, New York, NY, USA, 1993. View at: Google Scholar
  23. M. Zhou and K. Venkatesh, Modeling, Simulation and Control of Flexible Manufacturing Systems: A Petri Net Approach, World Scientific, Singapore, 1999. View at: Google Scholar
  24. J. A. Buzacott, “The fundamental principles of flexibility in manufacturing systems,” in Proceedings of the 1st International Conference on Flexible Manufacturing Systems, pp. 13–22, Brighton, UK, 1982. View at: Google Scholar
  25. J. A. Buzacott and D. D. Yao, “Flexible manufacturing systems: a review of analytical models,” Management Science, vol. 32, no. 7, pp. 890–905, 1986. View at: Google Scholar
  26. A. K. Sethi and S. P. Sethi, “Flexibility in manufacturing: a survey,” International Journal of Flexible Manufacturing Systems, vol. 2, no. 4, pp. 289–328, 1990. View at: Publisher Site | Google Scholar
  27. N. Viswanadham, Y. Narahari, and T. L. Johnson, “Stochastic modelling of flexible manufacturing systems,” Mathematical and Computer Modelling, vol. 16, no. 3, pp. 15–34, 1992. View at: Publisher Site | Google Scholar | Zentralblatt MATH
  28. M. Barad and S. Y. Nof, “CIM flexibility measures: a review and a framework for analysis and applicability assessment,” International Journal of Computer Integrated Manufacturing, vol. 10, no. 1–4, pp. 296–308, 1997. View at: Google Scholar
  29. A. De Toni and S. Tonchia, “Manufacturing flexibility: a literature review,” International Journal of Production Research, vol. 36, no. 6, pp. 1587–1617, 1998. View at: Publisher Site | Google Scholar | Zentralblatt MATH
  30. R. Beach, A. P. Muhlemann, D. H. R. Price, A. Paterson, and J. A. Sharp, “A review of manufacturing flexibility,” European Journal of Operational Research, vol. 122, no. 1, pp. 41–57, 2000. View at: Publisher Site | Google Scholar | Zentralblatt MATH
  31. D. Shi and R. L. Daniels, “A survey of manufacturing flexibility: implications for e-business flexibility,” IBM Systems Journal, vol. 42, no. 3, pp. 414–427, 2003. View at: Google Scholar
  32. Y. K. Son and C. S. Park, “Economic measure of productivity, quality and flexibility in advanced manufacturing systems,” Journal of Manufacturing Systems, vol. 6, no. 3, pp. 193–207, 1987. View at: Google Scholar
  33. F. F. Chen and E. E. Adam Jr., “The impact of flexible manufacturing systems on productivity and quality,” IEEE Transactions on Engineering Management, vol. 38, no. 1, pp. 33–45, 1991. View at: Publisher Site | Google Scholar
  34. N. Van Hop and K. Ruengsak, “Fuzzy estimation for manufacturing flexibility,” International Journal of Production Research, vol. 43, no. 17, pp. 3605–3617, 2005. View at: Publisher Site | Google Scholar | Zentralblatt MATH
  35. G. Da Silveira, D. Borenstein, and F. S. Fogliatto, “Mass customization: literature review and research directions,” International Journal of Production Economics, vol. 72, no. 1, pp. 1–13, 2001. View at: Publisher Site | Google Scholar
  36. P. G. Hoel, S. C. Port, and C. J. Stone, “Introduction to Stochastic Processes,” Houghton Mifflin, Boston, Mass, USA, 1972. View at: Google Scholar | Zentralblatt MATH | MathSciNet
  37. J. Li and N. Huang, “A Markovian model to evaluate quality performance in flexible manufacturing systems,” Tech. Rep. R&D-10274, General Motors Research & Development Center, Warren, Mich, USA, 2005. View at: Google Scholar

Copyright © 2007 Jingshan Li and Ningjian Huang. 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.


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