Towards self-optimizing and self-adaptive milling processes

This paper presents a novel control architecture system which is composed of a multi-objective cost function which Pareto optimises the programming of cutting parameters while adapting the milling process to new cutting conditions if new constraints appear. The paper combines a self-optimised module which looks for and finds Pareto optimal cutting parameters according to multi-objective purposes and, a multi-estimation adaptive control module which keeps the cutting forces under prescribed upper safety limits independently of programmed cutting conditions and material properties while maintaining the performance of the process. A supervised controller acts as decision support-software to automatically switch to best performance tracking adaptive controller among those available at each required time.