A Multiresponse Optimization Model for Statistical Design of Processes with Discrete Variables

Abstract

In manufacturing and diverse industries, quality has a main role to increase the market share. Hence, producers focus their attention to design products or services with high quality to meet the customer's expectations. Quality characteristics of products usually expressed by variables called response variables. Today's complex systems have several performance attributes in responses and designers try to select the best combination of controllable factors that satisfies all quality characteristics simultaneously. Since there are often several conflicts in quality characteristics, such as measurement units, scale and optimality directions, there are different approaches in model building and optimization of multi response surface problems. Therefore, the study of simultaneous analysis and improvement methods of the outputs are of great importance.