Design of Experiments
A statistical methodology for designing, conducting and analyzing experiments or tests to evaluate product and process design parameters or factors that affect the achievement of a product performance characteristic. The response of interest is evaluated under the various conditions to: (1) identify the influential variables among the ones tested, (2) quantify the effects across the range represented by the levels of the variables, (3) gain a better understanding of the nature of the causal system at work in the process, and (4) compare the effects and interactions. These experiments lead to setting parameter or factor levels (values) that can optimize the product performance characteristic under study and minimize the affects of variation. There are several techniques including Taguchi Methods, fractional factorial, and Plackett-Burman. DOE's are often classified in one of three categories: Screening Designs, which are intended to identify which main effects (factors) are the vital few important factors that require further study (usually a fractional factorial), Characterization Designs, which are used to gain some quantitative understanding of the relationships among the factors, including interactions, on the response variable (usually a factorial), and Optimization Designs, which are used to gain a precise understanding of the mathematical relationships that is sufficient to allow prediction and optimization throughput the experimental region.
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