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IEM 4113 - Industrial Experimentation
Prerequisite(s): 3103. Analytical methods for the purpose of process improvement. Experimental designs including single, blocked and multiple factors. Introduction to fractional factorial designs, central composite designs, and Taguchi robust designs. Data collection , analysis, and interpretation, including graphical methods, confidence intervals, and hypothesis tests. Multiple linear regression analysis methods. Industrial applications.
Monday, August 21, 2017 to Friday, December 8, 2017
67151 (undergraduate credit), 67152 (graduate credit)
*If graduate student taking this course, enroll in CRN 67152 for graduate credit.
Response Surface Methodology: Process and Product Optimization Using Designed Experiments.