Energy and CO2 emissions modeling for unconventional machining industry considering processing characteristics

Unconventional machining of WEDM (Wire Electrical Discharge Machining) is playing an increasingly important role in the manufacturing industry. The processing efficiency and resource consumption of this method are research hotspots from the perspective of sustainable development. Energy and CO2 emissions modeling of process machining have been recognized as an effective and economical ways to achieve energy-saving, emission-reducing and to improve process efficiency. However, the predictive modeling of energy and CO2 emissions in unconventional machining of WEDM machining has not been thoroughly fully studied. This paper proposes a predictive model of energy consumption and CO2 emissions in WEDM process considering process characteristics. The application of the energy and CO2 emissions model proposed in this paper in an example shows that the model's energy consumption prediction accuracy for single part processing reaches 96.5%, and the energy consumption prediction accuracy for batch processing is above 99%. A new standard for cutting fluid substitution with the best machining stability and energy consumption is proposed. In the example, it is also shown that the corners in the geometric structure will reduce the processing energy consumption. The smaller the number of single folding angles, the more energy consumption will be reduced. The processing energy consumption per unit area has a greater deviation when the thickness is low, and the thickness of the workpiece will also affect the life of the electrode wire. It depends on the number of multi-layer stacks and the life of electrode wires; the quality of machine tool auxiliary materials has a greater impact on energy consumption, with a difference of up to 40% in energy consumption. The results of this research can better understand the energy consumption and CO2 emissions characteristics of the unconventional machining of WEDM. [Display omitted] •Establish a predictive model of energy consumption and CO2 emissions•The corners in the geometric structure will reduce the energy consumption of processing.•The processing energy consumption per unit area has a large deviation when the thickness is low.•The quality of machine tool auxiliary materials has a greater impact on energy consumption.