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Estimating the energy model of machining process at the process design phase has been recognized as an effective method for energy-saving and emission reduction in manufacturing. Wire electrical discharge machining(WEDM) is a non-traditional machining and widely used in aerospace, automobile, medical, tool, and die manufacturing industries. In WEDM, energy consumption and energy efficiency are different with electrical parameter control strategy, and energy modeling and minimizing energy control strategy of WEDM are often ignored at process design phase. To bridge this gap in WEDM life cycle, an energy model of WEDM is established based on the requirements of low-energy consumption at process design phase. Moreover, a minimizing energy electrical parameter control strategy is recommended by calculating energy at the process design phase, which results in lower energy consumption and better energy efficiency compared with conventional strategy. In addition, it has great performance in reducing processing time. Significantly, based on the experimental investigations and thereafter analysis of the test results, the total energy consumption and processing time are reduced by 21.94% and 28.23%, respectively. [ABSTRACT FROM AUTHOR]

The scientific and reasonable prediction of energy consumption in WEDM process is the key for energy-saving optimization of wire-cutting process in the design stage. The existing research about WEDM energy-saving studies mainly focus on the pulsed power control strategies. And, the research on non-pulsed energy consumption of WEDM is deficient. The non-pulsed energy consumption takes up a larger proportion in the whole WEDM process through theoretical analysis and case verification, and the energy consumption characteristics are equally representative. Therefore, the paper analyzes the energy characteristics based on non-pulsed energy consumption subunits of WEDM. A non-pulsed auxiliary energy consumption and feeding energy prediction model is established, and a WEDM machine tool is used for the experiment. The accuracy of the prediction model proposed in this paper can reach more than 96%. The raise and establishment of the model provides the basis for energy saving optimization of the subsequent wire cutting process. [ABSTRACT FROM AUTHOR]