Development of Temperature Statistical Model when Machining of Aerospace Alloy Materials

This paper presents to develop first-order models for predicting the cutting temperature for end-milling operation of Hastelloy C-22HS by using four different coated carbide cutting tools and two different cutting environments. The first-order equations of cutting temperature are developed using the response surface methodology (RSM). The cutting variables are cutting speed, feed rate, and axial depth. The analyses are carried out with the aid of the statistical software package. It can be seen that the model is suitable to predict the longitudinal component of the cutting temperature close to those readings recorded experimentally with a 95% confident level. The results obtained from the predictive models are also compared with results obtained from finite-element analysis (FEA). The developed first-order equations for the cutting temperature revealed that the feed rate is the most crucial factor, followed by axial depth and cutting speed. The PVD coated cutting tools perform better than the CVD-coated cutting tools in terms of cutting temperature. The cutting tools coated with TiAlN perform better compared with other cutting tools during the machining performance of Hastelloy C-22HS. It followed by TiN/TiCN/TiN and CVD coated with TiN/TiCN/Al2O3 and TiN/TiCN/TiN. From the finite-element analysis, the distribution of the cutting temperature can be discussed. High temperature appears in the lower sliding friction zone and at the cutting tip of the cutting tool. Maximum temperature is developed at the rake face some distance away from the tool nose, however, before the chip lift away