A NOVEL BWM INTEGRATED MABAC DECISION-MAKING APPROACH TO OPTIMIZE THE WEAR PARAMETER OF CRN/TIALSIN COATING

Abstract

Using a multi-criteria decision-making (MCDM) method combined with a Taguchi (L16) design of experiment, the wear parameter for CrN/TiAlSiN coated hardened DAC-10 tool steel is optimized. Temperature, sliding velocity, applied load, and sliding distance together forms the wear parameter. Wear rate, friction coefficient, surface roughness, wear depth, and worn surface hardness were all tested to see how it affected by the wear parameters. The criteria weight was derived using the best-worst method (BWM) and combined with the Multi-Attributive Border Approximation area Comparison (MABAC) approach to rank the alternatives. The obtained data were then subjected to sensitivity testing using three-phase techniques. The suggested MCDM technique was validated through all phases of sensitivity analysis, with alternative WP6 (T = 100°C, Sv = 0.05 m/s, L = 5 N, and Sd = 2000 m) showing as the best alternative. Furthermore, the proposed method BWM-MABAC was tested on previously published outcomes, and the results showed an excellent correlation between present and past studies, with a rank correlation coefficient value of greater than 0.99.