Advertisement

Uniformity of Production vs. Conformance to Specifications in the Canning Problem

  • F. J. Arcelus

Abstract

This paper analyses an issue of great practical importance for many production processes, namely how to coordinate the apparently contradictory goals of producing not only in accordance to specifications but also with as much uniformity as possible in the characteristic of interest. The primary objective is to assess the viability of combining the twin quality objectives of minimizing rejection rates and maximizing the uniformity of production of the resulting items. The basic import of the study is that, when flexibility in setting specification limits and non-uniformity penalties exists, optimal results can be obtained which yield approximately the same profit per unit as that associated with the traditional within-specifications policy, while at the same time providing lower rejection rates and decreases in process variability.

Key Words

Quality Variance Reduction Taguchi Penalty Function Conformance-to-Specifications Optimization 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Arcelus, F.J. and P.K. Banerjee, “Optimal Production Plan in a Tool Wear Process with Rewards for Acceptable Undersized and Oversized Parts,” Engineering Costs and Production Economics, 11(1), pp 13–19, 1987.CrossRefGoogle Scholar
  2. [2]
    Arcelus, F.J. and M.A. Rahim, “Reducing Performance Variation in the Canning Problem, European Journal of Operational Research, accepted, 1996.Google Scholar
  3. [3]
    Easterling, R.G., M.E. Johnson, T.R. Bement and C.J. Nachtsheim, “Statistical Tolerance Based on Consumer’s Risk Considerations,” Journal of Quality Technology, 23, pp 1–11, 1991.Google Scholar
  4. [4]
    Golhar, D.Y. and S.M. Pollock, “Determination of the Optimal Process Mean and the Upper Limit for a Canning Problem,”, Journal of Quality Technology, 20, pp 188–192, 1988.Google Scholar
  5. [5]
    Golhar, D.Y. and S.M. Pollock, “Cost Savings Due to Variance Reduction in a Canning Process,” LIE Transactions, 24, pp 89–92, 1992.Google Scholar
  6. [6]
    Kackar, R.N., “Taguchi’s Quality Philosophy: Analysis and Commentary,” Quality Progress, December 21–29, 1986.Google Scholar
  7. [7]
    Lee, W.J. and T.C. Woo, “Optimum Selection of Discrete Tolerance,” Transactions of ASME, Journal of Mechanisms, Transmissions and Automation in Design, 111(2), pp 243–251, 1989.CrossRefGoogle Scholar
  8. [8]
    MATLAB, Optimization Toolbox,The Mathworks Inc., Natick, MA.Google Scholar
  9. [9]
    McClish, W.P., “Statistical Process Control - An Eye Opener,” Proceedings of Ceramic Engineering and Science, pp 557–563, 1983.Google Scholar
  10. [10]
    McClish, W.P., “Use of Statistical Controls in Production,” Proceedings of Ceramic Engineering and Science, pp 165–171, 1985.Google Scholar
  11. [11]
    Melloy, B.J., “Determining the Optimal Process Mean and Screening Limits for Packages Subject to Compliance Testing,” Journal of Quality Technology, 23(4), pp 318–323, 1991.Google Scholar
  12. [12]
    Montgomery, D.C., “The Use of Statistical Process Control and Design of Experiments in Product and Process Improvement,” IIE Transactions, 24, pp 4–17,1992.CrossRefGoogle Scholar
  13. [13]
    Ross, P.J., Taguchi Techniques for Quality Engineering, New York, McGraw Hill, 1988.Google Scholar
  14. [14]
    Singpurwalla, N.D., “A Bayesian Perspective on Taguchi’s Approach to Quality Engineering and Tolerance Design,” IIE Transactions, 24, pp 1827, 1992.CrossRefGoogle Scholar
  15. [15]
    Taguchi, G. “Quality Engineering in Japan,” Communications in Statistics: Theory and Methods, 14, pp 2785–2801, 1985.CrossRefGoogle Scholar
  16. [16]
    Taguchi, G. Introduction Quality Engineering, Asian Productivity Organization, Tokyo, 1986.Google Scholar
  17. [17]
    Taguchi, G., and D. Clausing, “Robust Quality,” Harvard Business Review, 68, pp 65–75, 1990.Google Scholar
  18. [18]
    Taguchi, G., E.A. Elsayed and T. Hsiang, Quality Engineering in Production Systems, McGraw Hill, New York, 1988.Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • F. J. Arcelus
    • 1
  1. 1.Faculty of AdministrationUniversity of New BrunswickFrederictonCanada

Personalised recommendations