In this research work, prognosis and diagnosis of tool wear for the polycrystal diamond (PCD) tool has been done by using fuzzy logic and Echostate Neural Network during machining of Al6061 metal matrix composite. Diagnosis refers to estimation of amount of tool worn out and prognosis refers to estimation of remaining tool life. The performances of fuzzy logic and ESNN with respect to diagnosis and prognosis of PCD tool wear has been compared.

Keywords: Fuzzy logic, Echostate neural network, Prognosis, Diagnosis, Tool wear