Screening Experiments for Dispersion Effects

Dizza Bursztyn () and David M. Steinberg ()
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Dizza Bursztyn: Ashkelon College
David M. Steinberg: Tel Aviv University, Department of Statistics and Operations Research

Chapter 2 in Screening, 2006, pp 21-47 from Springer

Abstract: Abstract Reduction of the variability in performance of products and manufacturing processes is crucial to the achievement of high levels of quality. Designed experiments can play an important role in this effort by identifying factors with dispersion effects, that is, factors that affect performance variability. Methods are presented for the design and analysis of experiments whose goal is the rapid screening of a list of candidate factors to find those with large dispersion effects. Several types of experiments are considered, including “robust design experiments” with noise factors, and both replicated and unreplicated fractional factorial experiments. We conclude that the effective use of noise factors is the most successful way to screen for dispersion effects. Problems are identified that arise in the various analyses proposed for unreplicated factorial experiments. Although these methods can be successful in screening for dispersion effects, they should be used with caution.

Keywords: Location Model; Dispersion Model; Dispersion Effect; Screening Experiment; Noise Factor (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-28014-1_2

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DOI: 10.1007/0-387-28014-6_2

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