Efficient and Cost Effective Response Surface Designs for Product and or Process Optimization

Abstract

Designing an experiment is an essential component of any scientific investigation. Experimental design aids in finding the conditions which are most favorable for particular characteristics (response). In erstwhile, the traditional one-factor-at-a-time (OFAT) and classical design of experiment (DOE) or factorial design are the two different strategies used for screening and optimization of any product and process system. The traditional OFAT approach examines only one parameter at a time while keeping other parameters constant and does not estimate interaction which results in inadequate optimization. On the other hand, however, DOE allows us to identify both the significant factor and important interactions among the factor in the fewer test than OFAT. It fails to predict the best factor level settings to meet the desired goal (minimum/maximum/desired responses) in the experimental region. The limitations of the classical method are eliminated by optimizing all the affecting variables collectively using response surface methodology (RSM) introduced by Box and Wilson (1951). newline