Design Method of Equipment Carbon Emission Monitoring System Driven by Carbon Footprint Knowledge in Manufacturing Process

doi:10.3901/JME.2025.02.395

Abstract

Abstract: With the development of intelligent manufacturing and sensor, it provides methods to actively obtain manufacturing process information, for low energy consumption and green manufacturing process in the “carbon peaking and carbon neutrality” policy. Considering the carbon emission data acquisition, analysis and feedback optimization in key equipment’s usage, based on the carbon emission model of manufacturing process, the Carbon footprint knowledge is obtained, the design method of equipment carbon emission monitoring system driven by Carbon footprint knowledge in manufacturing process is proposed. First, after analyzing the carbon emission process model of equipment’s manufacturing process, the Carbon footprint knowledge expression is presented based on carbon emission-performance variable, to obtain the performance monitoring requirements of equipment carbon emission information. Secondly, based on online monitoring and intelligent manufacturing systems, the acquisition methods and feature structures of various state variables are discussed, and the monitoring model of manufacturing process is established. Then, with analyzing the technical and economic cost in monitoring requirements of carbon emission, the design method of equipment carbon emission monitoring system driven by Carbon footprint knowledge in the manufacturing process is proposed. Finally, considering the usage of heavy-duty forming equipment, the online monitoring system is designed and proposed to verify the effectiveness of the proposed method.

Key words: carbon emission monitoring, manufacturing process, carbon footprint knowledge, monitoring system design

CLC Number:

TH164

KE Qingdi, CUI Huatao, ZOU Xiang, BAO Hong, HUANG Haihong. Design Method of Equipment Carbon Emission Monitoring System Driven by Carbon Footprint Knowledge in Manufacturing Process[J]. Journal of Mechanical Engineering, 2025, 61(2): 395-406.

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