A novel energy evaluation approach of machining processes based on data analysis

Energy shortages, air pollution, and stringent environmental requirements have been gaining increasing concern. Since the scarcity of energy resources, it is imperative to consider the economic and environmental issues of growth in manufacturing. This paper presented an energy evaluation method (considering cutting edges, workpiece hardness, material removal rate, and rotation speed) for machining system based on the group method of data handling (GMDH) algorithm. First, a response surface experimental was carried out with three materials to determine whether the cutting edges, workpiece hardness, spindle speed, and material removal rate (MRR) affect the processing energy. It was concluded that cutting edges number and hardness obviously have a significant influence on energy consumption. Then, further experimentations were designed, and an evaluation model of the electrical energy demand based on GMDH algorithm has been proposed, in which the application in a milling machine tool indicates that the predicted output values were found to correlate closely with the measured values. Finally, the proposed model is applied to a workpiece machining process, and the results show that the approach presented in this paper is effective, and hence, this paper provides an important addition to existing machining processes energy-evaluating methods.