A design of experiment is a structured, organized method for determining the relationship between factors (Xs) affecting a process and the output of that process. What distinguishes a design of experiment (DOE) from other methods is that input (factor) settings for the Xs are intentionally changed simultaneously in a prescribed manner to determine their effect on the process output. In traditional methods, data is generated in a trial-and-error manner, usually by changing only one factor at a time. This approach is more time-consuming and costly than using a designed experiment. It requires a great many runs and can not capture the combined effect of factors on the response.