Modification of extended Oxley’s predictive machining theory and determination of Johnson-Cook material model constants by inverse approach

Abstract

The Johnson-Cook (J-C) flow stress model, renowned for its consideration of the combined effect of strain, strain-rate, and temperature on material property, forms the cornerstone of this research. Its simplicity and applicability in numerical simulation render it widely popular. The study addresses two primary objectives: first, to modify extended Oxley’s predictive machining theory by eliminating the iterative loop for calculating the tool-chip interface temperature, and second, to utilize an inverse approach for determining J-C material model constants specific to medium carbon steel. The modified approach successfully eliminates the iterative loop, thereby streamlining the determination process and effectively reducing calculation time by 25%–40%, thereby enhancing overall efficiency. Concurrently, the study employs an inverse approach to accurately determine the J-C constants (A, B, n, C, and m). Notably, the research avoids the need for expensive and time-consuming Split Hopkinson Pressure Bar (SHPB) tests, instead opting for low-cost axial tensile tests and numerical optimization techniques to obtain the J-C constants. Thus, this study provides a practical method for determining J-C constants, pivotal for accurate material representation in numerical simulations and metal cutting applications. Standard materials and machines are employed, ensuring ease of understanding for a wider audience. The predicted values for the J-C constants are in proximity to the experimental values obtained by using SHPB test. Validated findings, achieved with precision under specified metal cutting conditions, highlight the effectiveness and applicability of the proposed approach, providing valuable insights for optimizing machining processes and improving efficiency.