Combined system for off-line optimization and adaptive cutting force control

The choice of manufacturing processes is based on cost, time and precision. A remaining drawback of modern CNC systems is that the machining parameters, such as feed-rate, cutting speed and depth of cut, are still programmed off-line. The machining parameters are usually selected before machining accordin to programmer's experience and machining handbooks. To prevent damage and to avoid machining failure the operating conditions are usually set extremely conservative. As a result, many CNC systems are inefficient and run under the operating conditions that are far from optimal . Even if the machining parameters are optimised off-line by an optimisation algorithm they cannot be adjusted during the machining process. In this paper, a neural adaptiv controller is developed and some simulations and experiments with the neural control strategy are carried out. The results demonstrate the ability of the proposed system to effectively regulate peak forces for cutting conditions commonly encountered in end milling operations