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Machining process modeling has been an active endeavor for more than a century and it has been reported to be able to predict industrially relevant process outcomes. Recent advances in the fundamental understanding of material behavior and material modeling aids in improving the sustainability of industrial machining process. In this work, the flow stress behavior of C45E steel is modeled by modifying the well-known Johnson-Cook model that incorporates the dynamic strain aging (DSA) influence. The modification is based on the Voyiadjis-Abed-Rusinek (VAR) material model approach. The modified JC model provides the possibility for the first time to include DSA influence in chip formation simulations. The transition from continuous to segmented chip for varying rake angle and feed at constant cutting velocity is predicted while using the ductile damage modeling approach with two different fracture initiation strain models (Autenrieth fracture initiation strain model and Karp fracture initiation strain model). The result shows that chip segmentation intensity and frequency is sensitive to fracture initiation strain models. The Autenrieth fracture initiation strain model can predict the transition from continuous to segmented chip qualitatively. The study shows the transition from continuous chip to segmented chip for varying feed rates and rake angles for the first time. The study highlights the need for material testing at strain, strain rate, and temperature prevalent in the machining process for the development of flow stress and fracture models.

In this study, the flow stress behavior of ferritic-pearlitic steel (C45E steel) is investigated through isothermal compression testing at different strain rates (1 s-1, 5 s-1, and 60 s-1) and temperatures ranging from 200 to 700 °C. The stress-strain curves obtained from experimental testing were post-processed to obtain true stress-true plastic strain curves. To fit the experimental data to well-known material models, Johnson-Cook (J-C) model was investigated and found to have a poor fit. Analysis of the flow stress as a function of temperature and strain rate showed that among other deformation mechanisms dynamic strain aging mechanism was active between the temperature range 200 and 400 °C for varying strain rates and J-C model is unable to capture this phenomenon. This lead to the need to modify the J-C model for the material under investigation. Therefore, the original J-C model parameters A, B and n are modified using the polynomial equation to capture its dependence on temperature and strain rate. The results show the ability of the modified J-C model to describe the flow behavior satisfactorily while dynamic strain aging was operative. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Cutting tool geometry design has traditionally relied on experimental studies; while engineering simulations, to the level of industrial deployment, have been developed only in the last couple of decades. With the development of simulation capability across length scales from micro to macro,cutting tool geometry development includes engineering data development for its efficient utilization. This calls for the design of a simulation-based approach in the design of cutting tool geometry so that the engineering data can be generated for different machining applications (e.g.digital twin). In this study, the needs for engineering model development of different stages of cutting tool design evaluation is assessed. To this end, some of the previously developed engineering models have been evaluated for evaluation of chip form morphology in industrially relevant nose turning process, work piece material behavior modeling and damage modeling for the prediction of chip shape morphology. The study shows the possibility for the developed models to act as building blocks of a digital twin. It also shows the need for engineering model development for different aspects of cutting tool design, its advantages, limitations, and prospects.

The finite element (FE) method based modeling of chip formation in machining provides the ability to predict output parameters like cutting forces and chip geometry. One of the important characteristics of chip morphology is chip segmentation. Majority of the literature within chip segmentation show cutting speed (vc) and feed rate (f) as the most influencing input parameters. The role of tool rake angle (α) on chip segmentation is limited and hence, the present study is aimed at understanding it. In addition, stress triaxiality’s importance in damage model employed in FE method in capturing the influence of α on chip morphology transformation is also studied. Furthermore, microstructure characterization of chips was carried out using a scanning electron microscope (SEM) to understand the chip formation process for certain cutting conditions. The results show that the tool α influences chip segmentation phenomena and that the incorporation of a stress triaxiality factor in damage models is required to be able to predict the influence of the α. The variation of chip segmentation frequency with f is predicted qualitatively but the accuracy of prediction needs improvement. © 2017 The Authors.