Application of finite element analysis and computational fluid dynamics in machining AISI 4340 steel

Abstract

AISI 4340 is a low-alloy steel with moderate carbon content that has garnered significant attention due to its remarkable properties, including high strength, toughness, and heat resistance. These characteristics make it highly desirable across industries such as construction, automotive, and aerospace. However, machining AISI 4340 poses substantial challenges due to the complex thermomechanical loading and high strain rates involved, which generate significant heat. This heat leads to accelerated tool wear, diminished productivity, and poor surface quality. High-speed machining (HSM) processes have shown promise in improving material removal rates and surface finish quality. However, the elevated temperatures in the cutting zone remain a critical concern, particularly in terms of tool durability. In response to these challenges, the development of virtual models has gained importance for reducing research time and costs. This review synthesizes relevant literature from the past decade, focusing on the application of Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) in machining processes involving AISI 4340 steel. It highlights the critical role of simulation techniques in optimizing machining processes, addressing key challenges, and improving overall operational efficiency and precision. For instance, FEA is extensively used for chip formation and machining response prediction, requiring careful consideration of cutting parameters and meshing quality to ensure accuracy. Meanwhile, CFD studies have primarily explored low cutting speeds and minimum quantity lubrication (MQL) systems, but not under high-speed cutting conditions. Most studies conducted have utilized FEA and CFD separately. Therefore, this review examines current trends and future directions, including the integration of CFD and FEA models for high-speed machining applications. Notably, most research on AISI 4340 machining has concentrated on improving cutting tools, optimizing cutting parameters, and advancing modelling techniques under dry machining conditions, but limited attention to coolant-assisted machining or Minimum Quantity Lubrication (MQL) application. Another identified research gaps, such as the limited exploration of integrated CFD-FEA models and high-speed machining under MQL conditions, provide avenues for future improvements in machining AISI 4340 steels.