Fuente: PubMed "swarm" Sci Rep. 2025 Nov 28;15(1):42719. doi: 10.1038/s41598-025-26719-1.ABSTRACTThe multi criteria decision analysis (MCDA) approach was used to optimise Abrasive waterjet (AWJ) pocket milling process parameters to examine the machinability of Ti-6Al-4 V alloy and the experiments were done by the L32 Taguchi array. Abrasive mesh (AM), waterjet pressure (WP), and traverse speed (TS) were chosen for this study, and material removal rate (MRR), depth of cut (DC), undercut (UC), and surface roughness (SR) were studied. Furthermore, the multiparametric ANOVA was used to determine the statistical significance of milling parameters, and the spatial pattern of output response parameter values was statistically assessed to support process parameter selection. Finally, regression models were developed based on milling parameters and output. To estimate the optimum level of input parameters for multi-objective optimization criteria on milling, particle swarm optimization (PSO), moth-flame optimization (MFO), grey wolf optimization (GWO), and whale optimization algorithm (WOA) have been combined with the combinative distance-based assessment (CODAS) methodology and multi-objective optimization on the basis of ratio analysis (MOORA). Weights for output were assigned using the objective-based entropy weight-age approach. The entropy weights for DC, UC, SR, and MRR were 0.3255, 0.2312, 0.1837, and 0.2596, respectively. The MOORA method predicts the best ideal parameters and based on the assessment scores MFO algorithm outperformed the others in maximising DC and MRR while reducing UC and SRR.PMID:41315415 | PMC:PMC12663170 | DOI:10.1038/s41598-025-26719-1