Adaptive Control Program for Rough Turning Machining Processes

Abstract

Although much research have been carried out to study and evaluate theory of metal cutting and machining, unsatisfactory repetitive outcome was obtained with a wide domain of variability. Although numerical control (NC) technology of machine tools has contributed to the machining topic in terms of more flexibility, better surface quality and dimensional accuracy, and higher productivity, it still incapable to adapt to the dynamic conditions that result from continuous variations during cutting. Current CNC machines follow preprogrammed fixed feeds and speeds during each cutting segment. In contrast to NC procedures, adaptive control (AC) technique measures the process output (responses) in real time, and automatically adjusts and continuously tunes cutting feed and/or speed to the optimal levels during each operation so as to achieve some objectives under the imposed system constraints. In the current work, an adaptive control simulation strategy is proposed in which the core of the optimization routine is based on some mathematical empirical models that define the interrelationship between the system responses (output) and the operating conditions (speed and feed). These models independently define the targeted primary objective; the metal removal rate (MRR), the secondary objectives; wear or its rate, and the system constraints; cutting forces and machining power. Optimization strategy involves the search for the best operational speed and/or feed combination that maximizes the MRR while attaining the lowest possible edge wear and/or its rate (tool life) under system constraints of tolerable force level and available spindle power. While all previously developed AC approaches addressed only the cutting feed and its relevant force level in milling, the proposed mathematical-model based adaptive control system deals with the turning operation where the cutting speed, as the main controlling parameter of the edge wear, along with the feed are considered.