Performance Optimization of Novel Laser Hybrid Ultrasonic Vibration Assisted Micro Milling for Inconel 718

Miniaturization drives advanced manufacturing essential for next-generation systems using superalloys in aerospace, biomedical and microelectronics. Hybrid machining combines distinct processes to harness their individual strengths and overcome limitations. This experimental research explored the machinability of Inconel 718 through novel laser hybrid ultrasonic vibration-assisted micro-milling (L-UVAMM), utilizing fiber laser for preparing slots followed by micro-milling on the corresponding laser-generated pilot slots with uncoated and three different coated tools. Cutting speed, feed, depth of cut, tool coatings and amplitude considered as input variables across four discrete levels to design experiments using Taguchi L-16 orthogonal array to investigate their effect on key responses including surface roughness, tool wear, and burr formation. Analysis of Variance (ANOVA) and Grey Relational Analysis (GRA) identified the most significant parameters and determined the best input combinations. Uncoated tools displayed the least tool wear, TiSiN minimized burr height while TiAlN improved surface roughness and reduced burr width. ANOVA for the regression model revealed the tool type as the most crucial factor influencing responses with a contribution ratio of 45.76%. Response surface method optimized the regression model for optimum conditions, resulted in 43.96%, 27.18%, and 19.65% average reduction of surface roughness, tool wear, and burr formation, respectively.