Mixture response surface methodology for improving the current operating condition

현재의 공정조건을 향상시키기 위한 혼합물 반응표면 방법론

  • Lim, Yong-B. (Department of Statistics, Ewha Womans University)
  • 임용빈 (이화여자대학교 자연과학대학 통계학과)
  • Received : 2010.08.02
  • Accepted : 2010.08.26
  • Published : 2010.09.30

Abstract

Mixture experiments involve combining ingredients or components of a mixture and the response is a function of the proportions of ingredients which is independent of the total amount of a mixture. The purpose of the mixture experiments is to find the optimum blending at which responses such as the flavor and acceptability are maximized. We assume the quadratic or special cubic canonical polynomial model over the experimental region for a mixture since the current mixture is assumed to be located in the neighborhood of the optimal mixture. The cost of the mixture is proportional to the cost of the ingredients of the mixture and is the linear function of the proportions of the ingredients. In this paper, we propose mixture response surface methods to develop a mixture such that the cost is down more than ten percent as well as mean responses are as good as those from the current mixture. The proposed methods are illustrated with the well known the flare experimental data described by McLean and Anderson(1966).

Keywords

References

  1. 임용빈(2007). "2차 혼합물 반응표면 모형에서의 강건한 실험 설계". 응용통계연구 20호, pp.267-280.
  2. Khuri, A.I., Harrison, J.M. and Cornell, .A.(1999). Using Quantile Plots of he Prediction Variance for Comparing esigns for a Constrained Mixture egion: An Application Involving aertilizer Experiment", Applied tatistics, Vol. 48, pp. 521-532.
  3. Lim, Yong B. and Park, S.H.(2007). "Number of cycles in evolutionary peration", J. of Korean Statistical ociety, Vol.36, pp.201-208.
  4. Mclean, R.A. and Anderson, V.L.(1966). "Extremevertices design of mixture experiments", Technometrics, Vol. 8, pp.447-454. https://doi.org/10.2307/1266691
  5. Myers, R.H. and Montgomery, D.C.(2009). Response Surface Methodology, 3rd ed., iley, New York.
  6. Piepel, G.F. and Cornell, J.A.(1994). "Mixture experimental approaches: Exam-ples, Discussion and Recommandations", J. of Qual-ity Technology, Vol.26, p.177-196 https://doi.org/10.1080/00224065.1994.11979525
  7. Snee, R.D.(1985). "Computer-Aided design of experiments: some practical experiences", J. of Quality Technology, ol.17, pp.222-236 https://doi.org/10.1080/00224065.1985.11978972
  8. Stat-Ease(2005). Design-Expert, software or response surface methodology and mi-ture experiments, Version 7, Stat-Ease, inneapo-lis.
  9. Vining, G.G., Cornell, J.A. and Myers, .H.(1993). "A graphical approach for e-valuating mixture designs", Applied Sta-tistics, Vol.42, pp.127-138. https://doi.org/10.2307/2347415