A comparative assessment of multicriteria parametric optimization methods for plasma arc cutting processes

Abstract

Plasma arc cutting (PAC) has evolved as an efficient process to cut complex profiles on many hard-to-machine engineering materials due to its many advantages, like higher dimensional accuracy, higher productivity, and the capability to cut thick materials. Optimization of this process is challenging due to existence of many input parameters, complex cutting mechanism, and interactions of the process parameters with the responses. In this paper, the applications of four newly developed multicriteria decision-making (MCDM) tools, i.e., Proximity Indexed Value (PIV), Evaluation by an Area-based Method of Ranking (EAMR), Pareto-Edgeworth Grierson (PEG), and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI) are presented for optimization of two PAC processes. To study the effects of criteria (response) weights on the optimization performance of the adopted MCDM techniques, two objective criteria weighting techniques, i.e., Criteria Importance Through Intercriteria Correlation (CRITIC) and Method based on the Removal Effects of Criteria (MEREC) are considered. All four MCDM techniques identify similar optimal parametric combinations at two different criteria weighting scenarios. The calculated Gini indexes also validate the superiority of the derived optimal parametric intermixes over the other experimental trials and similarity of the ranking performance of all four MCDM techniques.