Table of Contents
International Journal of Quality, Statistics, and Reliability
Volume 2009, Article ID 707583, 11 pages
http://dx.doi.org/10.1155/2009/707583
Research Article

Process Monitoring with Multivariate -Control Chart

Department of Economics and Statistics, University of Calabria, Via P. Bucci, cubo 0C, 87036 Rende, Italy

Received 6 September 2008; Revised 4 May 2009; Accepted 2 June 2009

Academic Editor: Myong (MK) Jeong

Copyright © 2009 Paolo C. Cozzucoli. 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.

Linked References

  1. E. Topalidou and S. Psarakis, “Review of multinomial and multiattribute quality control charts,” Quality and Reliability Engineering International. In press. View at Publisher · View at Google Scholar
  2. L. S. Nelson, “A chi-square control chart for several proportions,” Journal of Quality Technology, vol. 19, no. 4, pp. 229–231, 1987. View at Google Scholar
  3. H. Taleb and M. Limam, “On fuzzy and probabilistic control charts,” International Journal of Production Research, vol. 40, no. 12, pp. 2849–2863, 2002. View at Publisher · View at Google Scholar
  4. H. Taleb, “Control charts applications for multivariate attribute processes,” Computers and Industrial Engineering, vol. 56, no. 1, pp. 399–410, 2009. View at Publisher · View at Google Scholar
  5. A. J. Duncan, “A chi-square chart for controlling a set of percentages,” Industrial Quality Control, vol. 7, pp. 11–15, 1950. View at Google Scholar
  6. M. Marcucci, “Monitoring multinomial process,” Journal of Quality Technology, vol. 17, no. 2, pp. 86–91, 1985. View at Google Scholar
  7. M. Xie, T. N. Goh, and V. Kuralmani, Statistical Models and Control Charts for High Quality Processes, Kluwer Academic Publishers, Boston, Mass, USA, 2002.
  8. P. D. Bourke, “Detecting a shift in fraction nonconforming using run-length control charts with 100% inspection,” Journal of Quality Technology, vol. 23, no. 3, pp. 225–238, 1991. View at Google Scholar
  9. D. C. Montgomery, Introduction to Statistical Quality Control, John Wiley & Sons, New York, NY, USA, 2005.
  10. T. W. Calvin, “Quality control techniques for ‘zero- defects’,” IEEE Transactions on Components, Hybrids, and Manufacturing Technology, vol. 6, no. 3, pp. 323–328, 1983. View at Google Scholar
  11. F. C. Kaminsky, J. C. Benneyan, and R. D. Davis, “Statistical control charts based on a geometric distribution,” Journal of Quality Technology, vol. 24, no. 2, pp. 63–69, 1992. View at Google Scholar
  12. M. Xie and T. N. Goh, “Improvement detection by control charts for high yield processes,” International Journal of Quality and Reliability Management, vol. 10, pp. 24–31, 1993. View at Google Scholar
  13. C. P. Quesenberry, “Geometric Q charts for high quality processes,” Journal of Quality Technology, vol. 27, no. 4, pp. 304–315, 1995. View at Google Scholar
  14. M. Xie and T. N. Goh, “The use of probability limits for process control based on geometric distribution,” International Journal of Quality and Reliability Management, vol. 14, pp. 64–73, 1997. View at Google Scholar
  15. M. Xie, T. N. Goh, and L. Y. Chan, “A quality monitoring and decision-making scheme for automated production processes,” International Journal of Quality and Reliability Management, vol. 16, pp. 148–157, 1999. View at Google Scholar
  16. S. T. A. Niaki and B. Abbasi, “On the monitoring of multi-attributes high-quality production processes,” Metrika, vol. 66, no. 3, pp. 373–388, 2007. View at Publisher · View at Google Scholar
  17. X. S. Lu, M. Xie, T. N. Goh, and C. D. Lai, “Control chart for multivariate attribute processes,” International Journal of Production Research, vol. 36, no. 12, pp. 3477–3489, 1998. View at Google Scholar
  18. C. R. Cassady and J. A. Nachlas, “Evaluating and implementing 3-level control charts,” Quality Engineering, vol. 18, no. 3, pp. 285–292, 2006. View at Publisher · View at Google Scholar
  19. R. G. Miller, Simultaneous Statistical Inference, Springer, New York, NY, USA, 2nd edition, 1981.
  20. R. Z. Gold, “Tests auxiliary to χ2 tests in a Markov chain,” The Annals of Mathematical Statistics, vol. 34, no. 1, pp. 56–74, 1963. View at Google Scholar
  21. R. J. Serfling, Approximation Theorems of Mathematical Statistics, John Wiley & Sons, New York, NY, USA, 1980.
  22. L. A. Goodman, “On simultaneous confidence intervals for multinomial populations,” Technometrics, vol. 7, no. 2, pp. 247–254, 1965. View at Google Scholar
  23. Z. Šidàk, “Rectangular confidence regions for the means of multivariate normal distributions,” Journal of the American Statistical Association, vol. 62, pp. 626–633, 1967. View at Google Scholar
  24. Z. Šidàk, “On multivariate normal probabilities of rectangles: their dependence on correlations,” The Annals of Mathematical Statistics, vol. 39, pp. 1425–1434, 1968. View at Google Scholar
  25. A. J. Hayter and K.-L. Tsui, “Identification and quantification in multivariate quality control problems,” Journal of Quality Technology, vol. 26, no. 3, pp. 197–208, 1994. View at Google Scholar
  26. V. K. Rohatgi, An Introduction to Probability Theory and Mathematical Statistics, John Wiley & Sons, New York, NY, USA, 1976.
  27. W. G. Cochran, “Some methods for strengthening the common χ2 tests,” The Annals of Mathematical Statistics, vol. 10, no. 4, pp. 417–451, 1954. View at Google Scholar
  28. N. A. Heckert and J. Filliben, “NIST Handbook 148: DATAPLOT Reference Manual,” National Institute of Standards and Technology Handbook Series, 2003.