Dea Based Taguchi Approach for Multi-Objective Optimization in Machining Polymers: A Case Study

Abstract

Recently, fierce market competition has forced almost all manufacturing sectors to become more concerned on improved product quality in an economic way. Quality and productivity are two important but contradicting aspects of any manufacturing/ production process. Moreover, product quality is generally assessed by multiple indices. It is therefore, often required to optimize multiple quality features in order to determine the most favourable process environment before the product is subjected to undergo for mass production. Taguchi’s philosophy provides a trade-off between quality loss and productivity by engineering judgment. However, it fails to solve multi-objective optimization problem. In this context, Data Envelopment Analysis (DEA) can be applied as the means for converting multi-objectives into an equivalent single response; which can easily be optimized using Taguchi method. Application feasibility of proposed DEA based Taguchi method has been illustrated through a case study in which nylon have been machined using various process parameters (viz. cutting speed, feed rate and depth of cut) for optimizing material removal rate (MRR) and multiple surface roughness parameters of statistical importance.