Design and Implementation of an Effective Control Strategy for Metal Cutting Process

Abstract

In this paper, a mathematical model of cutting tool flank wear for the metal cutting process is used to evaluate a control approach for a nonlinear system. The dynamic cutting force and machining parameters work together to produce the flank wear model. When the flank wear model is calibrated to actual conditions, the nonlinear dynamic model is created. Many working conditions, such as softening and brittle fracture, cause tool failure during cutting and shorten the tool's lifespan. PID, PID based MPC, KALMAN and Extended KALMAN, Artificial Neural Networks, and Fuzzy Logic Controllers have been used in the paper work to manage the flank wear during the cutting process. The controller will be forced to limit the amount of tool ware, extending the life of the cutting tool.