The module introduces designed experiment as a tool for process improvements and designing products that are robust to environmental variability. Inferences about the effect of factors on a product or process can be drawn using designed experiment. Topics include analysis of variance of fixed-effect models, randomized block design, factorial designs, fractional factorial designs, blocking and confounding, response surface methodology, random effects models, nested and split-plot designs. Predictive analytics using designed experiments. This module is targeted at students who are interested in designing robust products and process improvements, and are able to meet the pre-requisites.
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