Speaker: Tirthankar Dasgupta, Georgia Tech

Abstract: In this paper, we discuss an integrated approach for estimation and reduction of measurement variation (and its components) through a single parameter design experiment. The noise factors are classified into a few distinct categories based on their impact on the measurement system. A random coefficients model that accounts for the effect of control factors and each category of noise factors on the signal-response relationship is proposed. A suitable performance measure is developed using this general model, and conditions under which it reduces to the usual dynamic signal-to-noise (SN) ratio are discussed. Two different data analysis strategies -- response function modeling (RFM) and performance measure modeling (PMM) -- for modeling and optimization are proposed and compared.

Tirthankar Dasgupta was a PhD student in ISyE working with Professor Jeff Wu. He is now a postdoc and will join Department of Statistics at Harvard University in the next year.

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