羊毛混纺面料生产流程的碳图谱建模与应用

Modeling of carbon footprints for producing wool blended fabrics and model applications

纺织行业绿色转型从原材料生产、纺纱、织造、染整到最终产品循环供应网络的链路长、碳足迹流向和分布极为复杂,面向全生命周期的绿色化碳追溯和管理非常困难。以羊毛混纺面料生产为研究对象,采用流程挖掘和图谱等工业智能技术,提出一种面料生产的碳图谱建模、碳排放量化和应用方法。首先,建立羊毛混纺面料各级工序流程中能量流、物料流、人员流和碳流4个维度的生产流程工序级别碳排放量化模型;其次,在量化模型基础上提出了一种羊毛混纺面料生产流程知识的碳图谱建模方法,可实现以订单为线索的面料生产流程工序碳排放计算;最后,利用流程挖掘技术生成直接跟随图,可视分析面料生产过程的全局碳排放分布与流向,可实现全局和局部碳排放多角度监测。以上海某纺织企业生产流程为例,进一步验证本文所提出的羊毛混纺面料生产流程碳排放图谱的有效性,以期为企业的碳减排工作提供指导和决策参考。

Objective In the context of the 2030 carbon peak target,the green transformation of the textile industry is the only way to achieve the carbon neutrality.However,the flow and distribution of carbon footprints are extremely complex,making green carbon tracing and management for the whole life cycle very difficult.This study aims to address the complex issue of tracing and managing the lifecycle carbon footprint of wool blended fabrics in the green transformation of the textile industry.The specific goal is to develop a carbon emission knowledge graph(simplified″carbon knowledge graph″)model for the production process of wool blended fabrics,quantify carbon emissions,and apply this model to provide guidance and decision-making support for the industry's carbon reduction efforts.Method The study employs industrial intelligent technologies such as process mining and knowledge graph.Initially,a carbon emission quantification model is developed considering four dimensions:energy flow,material flow,personnel flow,and carbon flow throughout the various stages of wool blended fabric production,facilitating the modeling of local-level carbon emission management.Subsequently,a carbon emission knowledge graph modeling approach is introduced on the foundation of the quantification model,which allows for the calculation of carbon emissions in fabric production processes.In the end,directly-follows graphs are produced to model the global-level carbon emission distribution throughout the fabric production process,accomplishing bidirectional modeling of both global-level and local-level carbon emissions.Results Using real data as an example,this paper constructs a carbon knowledge graph model for the production process of wool blended fabrics.The model comprises 8045 nodes,15717 edges,264 order nodes,and 779 process steps.The results show that the total carbon emissions for weaving in the current 264 orders amount to 385010.707 kg CO_(2),and the total carbon emissions for dyeing amount to 2385362.262 kg CO_(2).Therefore,analyzing the energy consumption,material usage,and personnel carbon emissions of the dyeing process in the production of wool blended fabrics is crucial for understanding its carbon footprint.Furthermore,a specific order case involving the dyeing process of a fabric blend of 80%wool,12%nylon,and 8%other fibers was selected for analysis.The experiment shows that the operation of production equipment is the main source of electrical energy carbon emissions in the actual production process,accounting for 93.92%of the total,or 1634.263 kg CO_(2).Moreover,the carbon emissions from the air compressor and lighting equipment were found to be 31.720 kg CO_(2) and 24.494 kg CO_(2),respectively.The results indicate that optimizing the carbon emissions of operating production equipment is key to reducing overall carbon emissions in the production process.In brief,the method proposed in this study has shown high effectiveness and feasibility in managing carbon emissions throughout the product lifecycle,providing an important reference for the field of low-carbon industrial manufacturing.Conclusion This study successfully proposes a method for carbon knowledge graph modeling,carbon emission quantification,and application for the production process of wool blended fabrics.The effectiveness of the model has been verified through real-world cases,and it provides guidance and decision-making support for its application in industry carbon emission reduction.The research approach is expected to be applied to other textile production processes,aiding in the green transformation of China's textile industry.