Modelling and optimization based on RSM in dry turning parameters of AISI H13 steel using novel hybrid design texture tool

Surface texturing on the cutting tool reduces friction in dry machining because high temperatures are recorded at the tool chip interface, resulting in excessive tool wear. This work focuses on the surface texturing of tungsten-coated carbide tools under dry machining of AISI H13 steel. Experiments were conducted using the principles of experimental design and predictive models are developed using the response surface methodology (RSM). The coefficient of determination (R2) for the measured output surface roughness (Ra) and tool-chip interface temperature (TCt) were 95% and 98%, respectively. The RSM-predicted models were in close agreement with the measured values. Desirability function approach (DFA) was used for the optimization and found the optimum values as Ra: 0.6685 μm and TCt: 156.95 °C at machining parameters such as cutting velocity: 125.6 m/min, federate: 0.12 mm/rev and depth of cut: 0.1 mm.