Response optimization and exploration are the challenging task in front of experimenter. The cause and effect of input variables on the responses can be found out after doing experiments in proper sequence. Generally relationship between response of interest y and predictor variables x1, x2, x3, … xk is formed after carefully designing of experimentation. For examples y might be biodiesel production from crude ‘Mahua’ and x1, x2 and x3 might be reaction temperature, reaction time and the catalyst feed rate in the process. In the present book chapter, design of experiment is discussed based on predictor variables for conducting experiments with the aim of building relationship between response and variables. Subsequently a case study is also discussed for demonstration of design of experiments for predicting surface roughness in the machining of titanium alloys based on response surface methodology.
Part of the book: Statistical Approaches With Emphasis on Design of Experiments Applied to Chemical Processes