A comparative study of analytical thermal models to predict the orthogonal cutting temperature of AISI 1045 steel

Abstract

Elevated temperature in the machining process is detrimental to the cutting tool due to a thermal softening effect. The increased material diffusion deteriorates the quality of the machined part. Experimental techniques and finite element method-based numerical models in temperature investigation are limited by the restricted accessibility and high computational cost respectively. Physic-based analytical models are developed to overcome those issues. This study investigated three analytical models, namely a modified chip formation model, Komanduri-Hou two heat sources model, and Ning-Liang material flow stress model, in the prediction of machining temperatures in orthogonal cutting. The evaluation and comparison between three models aim to promote the use of the analytical models in real applications, in which real-time prediction is highly appreciated. Temperatures in machining AISI 1045 steel were predicted under various cutting conditions. Acceptable agreements were observed between predictions and documented values in the literature. In the modified chip formation model, machining temperatures and forces were solved iteratively with complex mathematical equations, which reduced computational efficiency, and thus prevented a real-time temperature prediction. The heat partition factors were empirically determined, which resulted in unoptimized prediction accuracy. In Komanduri-Hou model, the input lengths of two shear zones and shear angle cannot be easily obtained from experiments due to the restricted accessibility. With the benefits of high prediction accuracy, high computational efficiency, and low experimental complexity of model inputs, Ning-Liang model was favored in the real-time prediction of machining temperatures.