Prediction of the cutting tool wear during dry hard turning of AISI D2 steel by using models based on Learning process and GA polyfit - Khaled Djellouli; Kamel Haddouche; Mostefa Belarbi; Zoubir Aich (The Journal of Engineering and Exact Sciences)
In this paper, we are interested in the prediction of flank wear through dry hard turning of AISI D2 steel with a mixed alumina insert. In the machining process, the cutting tool is principally affected by two kinds of wear: flank and crater wear. The latter are criteria for cessation of the tool function. In the absence of a real-time wear sensor, it is necessary to know or track wear with the view to prevent tool damage.