6_DoE_Intro_Xiao

6_DoE_Intro_Xiao - I nt r oduct ion t o E xper iment al...

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Introduction to Experimental Design Aug. 20, 2007
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Outline Traditional approach to determine an optimal process parameter Basic ideas of experimental design Statistical background Types of experimental design A simple example – RIE Design procedure and data analysis (with interactive examples) A screening experiment A response surface experiment Free resources Summary
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Am I using the optimum parameters? Experiment example: chemical synthesis Called a One-Factor- At-a-Time (OFAT) or Change-One- Separate-factor-at-a- Time (COST) strategy. Disadvantages: may lead to suboptimal settings requires too many runs to obtain good coverage of experimental region http://www.acc.umu.se /~tnkjtg/chemometrics /editorial/aug2002.pdf
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What do I do instead - Modern approach: DoE DoE = Design of Experiments (DoE) Design of experiments is the methodology of how to conduct and plan experiments in order to extract the maximum amount of information in the fewest number of runs. Key ideas: change several factors simultaneously use statistical analysis (Regression, ANOVA, with residual analysis, etc.) Obtain effect estimates; response surface; global optimum region Control and predict Statistical software (Minitab, SAS, Statgraphics, JMP, …) allows to choose or construct designs analyse experimental results
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