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Comparison of response surface model and Taguchi methodology for robust design

The principal objective of this study was to compare the results of a proposed
method based upon the response surface model to the Taguchi method. To modify the
Taguchi method, the proposed model was developed to encompass the following
objectives. The first, with the exception of the Taguchi inner array, was obtain optimal
design variable settings with minimum variations, at the same time achieving the target
value of the nominal-the best performance quality characteristics. The second was to
eliminate the need for the use of a noise matrix (that is, the Taguchi outer array),
resulting in the significant reduction of the number of experimental runs required to
implement the model. The final objective was to provide a method whereby signal-tonoise
ratios could be eliminated as performance statistics.
To implement the proposed method, a central composite design (CCD)
experiment was selected as a second-order response surface design for the estimation of
mean response functions. A Taylor's series expansion was applied to obtain estimated
variance expressions for a fitted second-order model. Performance measures, including
mean squared error, bias and variance, were obtained by simulations at optimal settings.
Nine test problems were developed to test the accuracy of the proposed CCD method.
Statistical comparisons of the proposed method to the Taguchi method were performed.
Experimental results indicated that the proposed response surface model can be used to
provide significant improvement in product quality. Moreover, by the reduction of the
number of experimental runs required for use of the Taguchi method, lower cost process
design can be achieved by use of the CCD method. / Graduation date: 1993

Identiferoai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/37196
Date01 December 1992
CreatorsSudasna-na-Ayudthya, Prapaisri
ContributorsMcDowell, Edward D.
Source SetsOregon State University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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