Modeling and Optimization of Cutting Parameters for Improved Tool Life in CNC Turning of AISI 1045 Steel

Abstract

Tool wear and cutting temperature are critical factors influencing machining efficiency and product quality in CNC turning operations. This study investigates the optimization of cutting parameters to maximize tool life while minimizing cutting temperatures during the machining of AISI 1045 medium carbon steel. Experiments were conducted using coated carbide inserts under varying cutting speeds (100–200 m/min), feed rates (0.1–0.3 mm/rev), and depths of cut (0.5–1.5 mm). Tool wear progression was monitored using optical microscopy, and cutting temperature was measured via embedded thermocouples. Analysis of variance (ANOVA) indicated that cutting speed had the most significant effect on both tool wear and temperature. Response surface methodology (RSM) was employed to develop predictive models, and optimization revealed that a cutting speed of 145 m/min, feed rate of 0.18 mm/rev, and depth of cut of 0.9 mm provided the best balance between tool life and thermal stability. Validation experiments confirmed the accuracy of the models, with predicted tool life within ±6% of experimental results. The findings contribute to improved process planning in CNC machining, reducing production costs and extending tool usability.