ABSTRACT
Over wear is one of the problems facing industry especially in the third world countries where storing conditions of inserts and workpieces are not ideal. The climates are completely different during day time and at night. The long storing time causes hardening of pieces specially those stored in open areas.
This paper proves that (Artificial intelligence) AI techniques were the key of designing a solution of the over wear problem. (Neural Network) NN proved ability to make more representing model of the turning process than the conventional methods of developing mathematical models. Data used for constructing this model were measured using an experiment of longitudinal turning performed on a CNC machine using force dynamometer of type TELC2010 with a cermet insert fixed to it, work pieces were of steel 52 [1].
Also, combination of expert system technique with conventional (Proportional Integral) PI controller using bumpless technique is the key of achieving acceptable behavior of the system under control.