数据驱动的制造业可持续性评估

doi:10.13196/j.cims.2022.08.005

计算机集成制造系统 ›› 2022, Vol. 28 ›› Issue (8): 2329-2342.DOI: 10.13196/j.cims.2022.08.005

数据驱动的制造业可持续性评估

张旭刚^1,2,陈洁^1,2,王玉玲^1,2,张华^1,2,江志刚^1,2,蔡维^3,4+

1.武汉科技大学冶金装备及其控制教育部重点实验室
2.武汉科技大学机械传动与制造工程湖北省重点实验室
3.西南大学工程技术学院
4.香港理工大学物流与航运系

出版日期:2022-08-31 发布日期:2022-09-19
基金资助:
国家自然科学基金资助项目(51605347,52075396)。

Data-driven manufacturing sustainability assessment

ZHANG Xugang^1,2,CHEN Jie^1,2,WANG Yuling^1,2,ZHANG Hua^1,2,JIANG Zhigang^1,2,CAI Wei^3,4+

1.Key Laboratory of Metallurgical Equipment and Control Technology,Ministry of Education,Wuhan University of Science and Technology
2.Hubei Provincial Key Laboratory of Mechanical Transmission and Manufacturing Engineering,Wuhan University of Science and Technology
3.College of Engineering and Technology,Southwest University
4.Department of Logistics and Maritime Studies,The Hong Kong Polytechnic University

Online:2022-08-31 Published:2022-09-19
Supported by:
Project supported by the National Natural Science Foundation,China(No.51605347,52075396).

摘要/Abstract

摘要： 针对制造业数据的多属性特征,构建了制造业数据驱动的多属性可持续性评估指标体系,首先基于主成分分析法获取各制造业分因素下的可持续性能评分,然后基于反向传播—决策试验与评价实验室的网络分析法确定数据属性间的综合权重、因果关系图和主要影响强度路径图,最后通过基于比率分析的多目标优化方法评估制造业当前的可持续性能与期望性能的差距比率并提出优化方向。结果表明,在分因素评估下,计算机、通信和其他电子设备制造业在经济和科技指标下得分最高,而金属制品、机械和设备修理业在环境指标下得分最高。从综合分析结果来看,仪器仪表制造业具有最大的可持续性能,并且仪器仪表制造业可致力于提高固定资产投资比率来提升行业的可持续性能。

关键词: 数据驱动, 可持续性评估, 制造业, 主成分分析法, 多目标优化

Abstract: Aiming at the multi-attribute characteristics of manufacturing data,the multi-attribute sustainability evaluation index system of manufacturing industry was constructed.The Principal Component Analysis (PCA) was used to evaluate the sustainable performance score of each manufacturing.Then Back Propagation-Dematel Analytic Network Process (BP-DANP) method was used to determine the comprehensive weightof data property,Influence Strength Network Relationship Map (ISNRM) and Critical Influence Strength Route (CISR).The gap between the current sustainable performance and the expected of the manufacturing industry was evaluated by using Multi-objective Optimization based on Ratio Analysis method (MOORA),and the optimizing direction was proposed.The results showed that the computer,communication and other electronic equipment manufacturing industry had the highest score under the economic and technological indicators,while the metal products,machinery and equipment repair industry had the highest score under the environmental indicators.The comprehensive analysis showed that the instrument manufacturing industry had the largest sustainable performance,and the instrument manufacturing industry could be committed to improving the ratio of fixed assets investment to improve the sustainable performance.

Key words: data driven, sustainable assessment, manufacturing industry, principal component analysis, multi-objective optimization

中图分类号:

TH162

张旭刚, 陈洁, 王玉玲, 张华, 江志刚, 蔡维. 数据驱动的制造业可持续性评估[J]. 计算机集成制造系统, 2022, 28(8): 2329-2342.

ZHANG Xugang, CHEN Jie, WANG Yuling, ZHANG Hua, JIANG Zhigang, CAI Wei. Data-driven manufacturing sustainability assessment[J]. Computer Integrated Manufacturing System, 2022, 28(8): 2329-2342.

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数据驱动的制造业可持续性评估

Data-driven manufacturing sustainability assessment

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