Energy consumption characteristic identification and energy-saving diagnosis methods for industrial production

Manufacturing is one of the major sectors of global energy consumption. With the rise in energy costs and the advancement of sustainable development goals, improving energy efficiency has become an urgent issue that manufacturing enterprises need to address. This paper proposes an energy consumption analysis method based on multiple characteristic parameters in view of the characteristics of complex energy consumption distribution and high difficulty in optimization existing in the manufacturing production process. The research conducts systematic modeling of the attributes, states and operations of the production process to construct a multi-parameter coupling model. The standby energy consumption ratio, production sensitivity, temperature influence factor and equipment efficiency index are dynamically embedded into the energy consumption prediction formula as characteristic parameters. The parameter combination is solved through optimization algorithms to achieve high-precision decomposition and prediction of production energy consumption and quantify the energy consumption characteristics. The case shows that the high temperature influence factor in the coating process and the insufficient efficiency of stamping and welding equipment in a certain factory were identified as optimization priorities. The estimated energy-saving potential was 66,400 kWh, accounting for 13.2% of the total production energy consumption. This method provides full-chain support for the manufacturing industry from energy consumption characteristic analysis to energy-saving decision-making.