Optimal variable screening in automobile motor-head machining process using metaheuristic approaches in the Mahalanobis-Taguchi System

The Mahalanobis-Taguchi System is a data analytical method for the diagnosis and/or pattern recognition with multivariate data and it is useful for quantitative decision making where the Mahalanobis distance plays a key role. Over time, MTS has received wide acceptance in the scientific community as well as in practical industry and it has been applied to different problems where variable screening of the original set of attributes is essential. In this paper, MTS is applied to an automobile motor-head machining process and the corresponding mathematical model for dimensional reduction is solved using metaherustic algorithms from swarm intelligence optimization.