Abstract
This paper focuses on the development of an empirical model for the use in soft sensors to predict the surface layer properties of AISI 52100 machined via cryogenic hard turning. By using response surface methodology, a multiple regression is performed to achieve correlations between the process parameters, the process forces and the temperature, as well as the residual stresses and the austenite content. The results show a predictive R2 of over 0.75 and indicate that the empirical model can be used in soft sensors for a process control of cryogenic hard turning.
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