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|Title:||An experience in analyzing process optimization data in the presence of unknown confounding||Authors:||Goh, T.N.||Keywords:||Confounding
Design of experiments
Fractional factorial design
|Issue Date:||1996||Citation:||Goh, T.N. (1996). An experience in analyzing process optimization data in the presence of unknown confounding. Quality Engineering 9 (2) : 299-304. ScholarBank@NUS Repository.||Abstract:||An account is given of a series of results encountered in a parameter design study conducted in the usual Taguchi-style optimization routine. With the benefit of hindsight it was realized that an unsuspected active interaction effect was the cause of various puzzling findings. One learns from this experience that such interactions could lead to not just suboptimal solutions, they could also give false indications of nonlinearity in a Taguchi analysis. A capability in aliasing structure analysis in fractional factorial design and mathematical modeling of parameter-response relations is therefore recommended highly to those who have stretched the Taguchi approach to the limit of its usefulness.||Source Title:||Quality Engineering||URI:||http://scholarbank.nus.edu.sg/handle/10635/63003||ISSN:||08982112|
|Appears in Collections:||Staff Publications|
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