Numerical investigation and experimental validation of the effects on response parameters in a cryogenic assisted turning of Nimonic C-263 alloy

Nickel based alloys are extensively used in critical engineering applications such as aerospace, marine, nuclear, defence, etc. owing to their unique set of characteristics such as excellent fatigue resistance, creep resistance, thermal stability, corrosion resistance, oxidation resistance, and the ability to be operated effectively at higher temperatures and pressures. However, due to their superior properties, nickel alloys are extremely difficult to machine, which brings up the need to modify the machining strategy of this alloy to take advantage of their unique properties. The machining strategy employed for maintaining the machining zone temperature involves adopting various resources, which incurs an excessive cost to any industry. As a result, the use of finite element modelling to simulate process parameters during machining is an extremely contentious topic at the present time. The numerical and experimental investigation of the cryogenic turning process is carried out to investigate the effect of process parameters on machining responses and measure the quality of machining during the turning of Nimonic C-263 superalloy. The numerical simulation is done using LS-Dyna software, and the simulated results were compared with experimental findings. The experimental results showed that with an increase in cryogenic temperature and soaking time, the cutting force and cutting temperature increased. The highest values of these responses are observed at higher speeds, a higher feed rate, and a higher cutting depth at the lowest temperature and soaking time. The findings from the simulation model are extremely comparable to the experimental results, with the standard minimum values of cutting forces and temperature in close agreement at 5.77% and 7.71%, respectively. Thus, it is important to note that the 3D FE model is effective and efficient for predicting and measuring outcomes with a minimal amount of error.