doi: 10.7763/IJCTE.2013.V5.706
Optimization of Correlated Multiple Response Surfaces with Stochastic Covariate
Taha Hossein Hejazi1
,
Ali Salmasnia2 ,
Mahdi Bastan3
- 1Department of Industrial Engineering and Management Systems,Amirkabir University of Technology,Tehran, Iran.
- 2Department of Industrial Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran.
- 3Department of Industrial Engineering, Faculty of Engineering, Eyvanakey University, Semnan, Iran.
Abstract
Optimizing quality engineering problems has become a common problem when there are several correlated product quality characteristics. Moreover, in design of experiments, controlling covariate effects could reduce error and uncovered variances as well as give more insight about the process. This work identifies process variables to analyze correlated multiple responses with stochastic covariates. It also considers dispersion effects and specification limits besides location effects in an integrated framework based on desirability function. At the end, efficacies of the proposed approach are assessed by a numerical example.
Keywords
- Design of experiments
- multiresponse optimization
- covariate effects
- principal component analysis
- and desirability function
How to Cite
Taha Hossein Hejazi, Ali Salmasnia, and Mahdi Bastan, "Optimization of Correlated Multiple Response Surfaces with Stochastic Covariate," International Journal of Computer Theory and Engineering, vol. 5, no. 2, pp. 341-345, 2013. https://doi.org/10.7763/IJCTE.2013.V5.706
Copyright & License
Copyright © 2013 by the authors. 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 (CC BY 4.0).