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공정변수를 갖는 혼합물 실험 자료를 활용한 최적조건 찾기에 관한 소고

A Note on Finding Optimum Conditions Using Mixture Experimental Data with rocess Variables

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주제분류학제간연구

초록

Purpose: Given the several proper models for given mixture components-process variables experimental data, we propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those models. Methods: Given the mixture experimental data with process variables, first we choose the reasonable starting models among the class of admissible product models based on the model selection criteria and then, search for the candidate models that are the subset models of the starting model by the sequential variable selection method or all possible regressions procedure. Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. Results: We propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those good candidate models by adopting the optimization methods developed in multiple responses surface methodology. Conclusion: A strategy is proposed to find the optimal condition in which the performance of the responses is well-behaved under those proper combined models. This strategy to find the optimal condition is illustrated with the example in this paper.

Abstract

Purpose: Given the several proper models for given mixture components-process variables experimental data, we propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those models. Methods: Given the mixture experimental data with process variables, first we choose the reasonable starting models among the class of admissible product models based on the model selection criteria and then, search for the candidate models that are the subset models of the starting model by the sequential variable selection method or all possible regressions procedure. Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. Results: We propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those good candidate models by adopting the optimization methods developed in multiple responses surface methodology. Conclusion: A strategy is proposed to find the optimal condition in which the performance of the responses is well-behaved under those proper combined models. This strategy to find the optimal condition is illustrated with the example in this paper.

참고문헌 (6)

  1. Cornell, John A., "Experiments with Mixtures" (2002), Wiley
  2. Dal Bello, L. H. A., "Optimization of a product performance using mixture experiments including process variables", Journal of Applied Statistics, 38, pp.1701~1715 (2011)
  3. 임용빈, "실용적인 혼합물 성분 공정변수 실험설계", 품질경영학회지, 39(3), pp.400~411 (2011), 한국품질경영학회
  4. 임용빈, "공정변수를 갖는 혼합물 실험 자료의 분석", 품질경영학회지, 40(3), pp.347~358 (2012), 한국품질경영학회[DOI]
  5. Myers, Raymond H., "Response Surface Methodology" (2009), Wiley
  6. Næs, Tormod, "A comparison of methods for analyzing data from a three component mixture experiment in the presence of variation created by two process variables", Chemometrics and Intelligent Laboratory Systems, 41, pp.221~235 (1998)

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