Data driven eco-efficiency evaluation and optimization in industrial production. (1st June 2021)

• Record Type: Journal Article
• Authors: Liu, Conghu; Gao, Mengdi; Zhu, Guang; Zhang, Cuixia; Zhang, Pan; Chen, Jianqing; Cai, Wei
• Is Part Of: Energy. Volume 224(2021)
• Publication Date: 2021-06-01
• Subjects: Eco-efficiency -- Industrial production -- Data driven -- Emergy -- Sustainability; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.120170
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: To improve the ecological efficiency (eco-efficiency) of industrial production and promote its sustainable development, we present a data-driven method for evaluating and optimizing the eco-efficiency of industrial production system. The data of industrial production system are collected and processed in a unified dimension from the perspective of emergy, then the eco-efficiency evaluation model of industrial production system is constructed to realize the quantitative evaluation, the correlation between various factors and eco-efficiency is analysed, and a date driven eco-efficiency optimization decision is built to improve eco-efficiency and production benefits in industrial production. In the application to an example in a manufacturing enterprise, the method identifies opportunity for reducing resource consumption by 8.3% and waste discharge by 6.7%, enhancing the eco-efficiency by 13.8% and production benefit by 8.1%. This paper provides theoretical and methodological support for the evaluation and optimization of eco-efficiency of industrial production system, and also provides theoretical basis for the sustainable development of industrial production. Highlights: Ecological efficiency of industrial production considering the economic, social and environmental benefits. Constructing a data-driven eco-efficiency model of industrial production system. Analysing various factors related to the eco-efficiency. Illustrating the measurable, evaluable and optimized eco-efficiency mechanism of industrial production system.