Surface model and tool-wear prediction model for solid lubricant-assisted turning

Abstract

Mathematical models for surface roughness and tool wear are developed through regression analysis of the experimental data collected from machining. Different particle sizes and flowrates of solid lubricants are employed in the study. Experimental results show a significant effect of solid lubricant particle size and flowrate on surface roughness and tool wear. Decrease in the particle size resulted in reduced tool wear and surface finish improvement. Various machining parameters such as cutting forces, tool wear, and surface roughness improved with an increase in the flowrate of solid lubricant up to a certain level and remained constant at higher flowrates. To estimate the effect of solid lubricants on machining, exponential models are proposed in the present work to predict tool wear and surface roughness as a function of solid lubricant particle size, flowrate, machining time, and cutting force. Predicted values obtained from the developed model and experimental results are compared, and error<10 per cent is observed.