An improved machining temperature prediction model for aerospace alloys: Effect of cutting edge radius and tool wear

Temperature rise during machining impacts the workpiece material properties, residual stresses, surface and sub-surface quality. Experimental, numerical, and analytical methods have been used to predict the temperature fields in the tool, workpiece and chip. Each approach has its limitations: experimental techniques are cumbersome with expensive equipment, and numerical modeling is computationally inefficient. Existing analytical models only consider the effect of wear while ignoring the edge radius, though the latter changes with the flank wear in practice. To address this limitation, this article proposes an improved analytical temperature prediction model for orthogonal machining by introducing discrete linear heat sources on the edge radius of the cutting edge. The model describes the machining deformation zones by moving or stationary heat sources and models the adiabatic surfaces by imaginary heat sources. The heat partition is calculated to describe the amount of temperature transferred from a heat source to a given body. A global coordinate system is introduced to facilitate the integration of the edge radius in the temperature model, and variation in the direction of the heat source velocity. Temperature predictions of the developed model were experimentally verified using an inverse method based on XRD residual stress measurements. The results of the analysis show that the proposed model is reasonably accurate and most importantly computationally efficient alternative to tedious experimental measurements or more complicated finite element approaches.