Modeling and Assessment of Power Consumption for Green Machining Strategy

Energy-saving technologies seek to minimize the environmental burden caused by manufacturing. In this study, it is aimed to develop a sustainable machining strategy that reduces the energy consumed during metal cutting, via modeling and assessment of power consumption of the process. Three perspectives, smart, optimal, and universal, are used to review the literature and define the strategic requirements. Based on the perspectives, the power consumption data was utilized to monitor the process in real-time and to control the process to be sustainable with a wide variety of cutting conditions and manufacturing environments. A power-prediction model was constructed, and two adaptive feed-control schemes were suggested. One controls the feed, while the other controls the feed per tooth. The experimental results show that both control schemes were up to 18% energy efficient with the given geometries and easily applicable over a wide range of conditions and satisfied the requirements set out above. The efficiencies of the control methods were discussed with respect to the control criteria, constraints, and materials. It is expected that this research will facilitate sustainable machining.