Robust parameter design using the weighted metric method - The case of 'the smaller the better'

• Autorzy: Ardakani M. K. , Noorossana R. , Niaki S. T. A. , Lahijanian H.
• Języki publikacji: EN

Abstrakty

EN

In process robustness studies, it is desirable to minimize the influence of noise factors on the system and simultaneously determine the levels of controllable factors optimizing the overall response or outcome. In the cases when a random effects model is applicable and a fixed effects model is assumed instead, an increase in the variance of the coefficient vector should be expected. In this paper, the impacts of this assumption on the results of the experiment in the context of robust parameter design are investigated. Furthermore, two criteria are considered to determine the optimum settings for the control factors. In order to better understand the proposed method and to evaluate its performances, a numerical example for the case of 'the smaller the better' is included.

Słowa kluczowe

EN

multiobjective decision making; regression estimation; response surface methodology; robust parameter design; weighted metric method

PL

wnioskowanie decyzyjne; estymacja regresji; metodologia oceny powierzchni; metoda metryczna

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2009
• Tom: Vol. 19, no 1
• Strony: 59--68
• Opis fizyczny: Bibliogr. 40 poz., tab., wykr.

Twórcy

autor

Ardakani M. K.

• Department of Civil Engineering The Catholic University of America, Washington DC 20064, USA

autor

Noorossana R.

• Department of Industrial Engineering Iran University of Science and Technology, Tehran, Iran

autor

Niaki S. T. A.

• Department of Industrial Engineering Sharif University of Technology, Tehran, Iran

autor

Lahijanian H.

• Department of Industrial Engineering Iran University of Science and Technology, Tehran, Iran

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