Multi-response optimisation using Grey relational analysis and Shainin design of experiments

Abstract

Several approaches are used for simultaneous optimisation of multi-response experiments to predict the significant parameters in the area of design of experiments. Researchers focus more on the mathematical models and numerical analysis to find the significant factors contribute to the problem statement both in problem solving approaches and process characterisation. Shainin proposed a set of tools and techniques to improve the quality both offline and online quality assurance. The purpose of using all these set of tools is to find the vital few dominant cause called red X and second dominant cause called pink X which affects the manufacturing system or quality assurance. This paper deals with the application of Grey relational analysis to combine the multi responses into a single response which affects the problem statement and predicts the optimum parameter levels for confirmation experiment. A case study is illustrated to explain the steps and discussed in detail. This shows the application feasibility of the Grey relational analysis with Shainin design of experiments in combination to improve the quality characteristics and process characterisation.