Application of Response Surface Methodology (RSM) as tool for the optimization of production processes in industries

Abstract

The concept of Response Surface Methodology (RSM) was systematically exposed for possible adoption by Scientists, Engineers and Industries. RSM is an empirical model which employs the use of mathematical and statistical techniques in relating input variables otherwise known as factors to the response. RSM became very useful due to the fact that other methods available such as the full factorial model could be very cumbersome to use, time-consuming, inefficient, error prone and unreliable. In an effort to obtain an objective conclusion between the factors and the response, an experimenter needs to plan and design the experiments, and analyze the results. An approximation of the response in relation to the variables is otherwise known as RSM. Some few methods used as Design of experiments were reviewed. RSM concept and design types were highlighted; some scenario applications of RSM in various fields were cited for easy understanding and adoption by researchers. The study concluded that RSM is a highly beneficial tool for finding optimum conditions to and for developing mathematical models that predicts the output (response) which depends on the combinations of parameters level. It also gives the opportunity for studying the parameters which affect the response as well as to project the relative magnitude and interaction between them. The use of RSM technique is the best technique for process modification, optimization and experimental analysis.