A study on the effects of objective weighting methods on TOPSIS-based parametric optimization of non-traditional machining processes

Abstract

Developing advanced engineering materials with enhanced mechanical and metallurgical properties has caused non-traditional machining (NTM) processes to emerge as cost-effective and energy-efficient options. Improper settings of the input parameters of those processes may often lead to inferior quality and accuracy of the finished products. Multi-criteria decision-making (MCDM) methods appear as potent tools for multi-objective optimization of those processes. Determining criteria weights is a crucial step in any MCDM problem; subjective approaches for evaluating criteria weights may result in inconsistent judgments. In this paper, the effects of ten different objective weighting methods, i.e., equal weight, entropy weight, Criteria Importance Through Inter-criteria Correlation (CRITIC), Method based on Removal Effects of Criteria (MEREC), Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), Symmetry Point of Criterion (SPC), Criteria Impact Loss (CILOS), Integrated Determination of Objective Criteria Weights (IDOCRIW), Principal Component Analysis (PCA) and Weighted Principal Component Analysis (WPCA) are studied on Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)-based optimization of two NTM processes. In the first example, the optimal parametric combination computed using equal weight, entropy, MEREC, LOPCOW, PCA, and WPCA is noticed to be the same. In contrast, a different set of optimal parameters is derived by applying CRITIC, SPC, CILOS, and IDOCRIW. In the second example, seven out of ten approaches obtain a unique set of parametric combinations, while CILOS, IDOCRIW, and PCA lead to a different set of intermixes. It can be concluded that the ranks of the experiment trials for both the examples are almost similar irrespective of the objective criteria weighting technique employed.