Evaluation of an Analytical Model in the Prediction of Machining Temperature of AISI 1045 Steel and AISI 4340 Steel

Abstract

This paper evaluates a physics-based analytical model in the prediction of machining temperature of AISI 1045 steel and AISI 4340 steel. The prediction model was developed based on the Johnson-Cook constitutive model (J-C model) and mechanics of the orthogonal cutting process. The average temperatures at two shear zones were predicted by minimizing the difference between calculated stresses using the J-C model and calculated stresses using the mechanics model. In this work, (1) the influence of input Johnson-Cook model constants, cutting force, and chip thickness on the accuracy of predictions are investigated with sensitivity analyses, in which multiple sets of available J-C constants and varying cutting force and chip thickness are used for the temperature prediction in machining AISI 1045 steel. The larger the input deviation, the larger prediction deviation. The temperature at the primary shear zone is more susceptible to the deviation of inputs than the temperature at the secondary shear zone. (2) The machining temperatures are also predicted in machining AISI 4340 steel using cutting tools with various specifications to demonstrate its predictive capability. Good agreements are observed upon validation to available experimental data in the literature. (3) Lastly, the advantage and limitation of the temperature model are discussed with comparison other analytical temperature models. Considering the reliable and easily measurable input requirements and sufficient predictive capability, this temperature model can be employed for effective and efficient machining temperature prediction.

Towards Optimization of Machining Performance and Sustainability Aspects when Turning AISI 1045 Steel under Different Cooling and Lubrication Strategies

“…It was found that only a limited amount of improvement was achieved (around 4.32%) [16]. Furthermore, in the open literature [17,18] some analytical constitutive relations were proposed to predict the machining temperatures generated when turning AISI 1045 steel. The computed model was very efficient, which permits real-time prediction and reduced experimental complexity for the input variables.…”

Experimental-Analytical Method for Temperature Determination in the Cutting Zone during Orthogonal Turning of GRADE 2 Titanium Alloy

“…The majority of the model-based (J-C, Oxley’s) analytical methods use the assumptions: 1—cutting tool is perfectly sharp and not worn, 2—chip forming process is continuous, 3—the heat flux loss as a result of convection and radiation from the surface of the workpiece, tool, and chip are negligible, 4—chip thickness over the entire contact area with the rake face is constant, 5—the directions of slip forces and of the force tangential to the tool rake face are collinear to the respective directions of the slip and chip speed vectors. Adequate knowledge of the contact temperature in the cutting zone at specific conditions is an important element in determining the thermo-mechanical cutting process [ 23 , 24 , 25 , 26 , 27 ]. The use of analytical method for determination of temperature in the SSZ was presented by Chen et al [ 28 ].…”

Predictive Modeling of Machining Temperatures with Force–Temperature Correlation Using Cutting Mechanics and Constitutive Relation

“…For comparison, the analytical model reported in the previous work used the chip-thickness and constant-material-flow-rate assumption that prevents real-time temperature prediction and optimized prediction accuracy [29]. More details of the previous model and its predictive capability can be found in reference [30]. The experimental techniques and developed models used to investigate the machining process are summarized in Table 1.…”