2015 QPRC
Holistic DOE: Learning in the Face of Uncertainty
Abstract Text:
Holistic DOE will show how advancements in analytic tools can help consistently meet customer requirements in the face of uncertainty. Methods will be shown on how to use observational sources of data in order to create better future experiments.
Topics covered are:
- How to get the most from large and messy data, even with missing information
- How to use modern screening approaches to find the right potential drivers of performance
- How to compare the potential drivers of performance to pick the best ones for further experimentation
- How to select the right types of experiments to get optimized results with the lowest experimental cost
Relevant case studies will be used to show first hand how Holistic DOE approaches drive superior results across common application areas.
Keywords: Screening, Modeling, Experimentation, Data Mining, DOE
AUTHORS
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1: Wise, Scott - SAS Institute, Inc. (presenting)
2: Dan Valente – SAS Institute, Inc. (presenting)