Data driven eco-efficiency evaluation and optimization in industrial production

Conghu Liu, Mengdi Gao, Guang Zhu, Cuixia Zhang, Pan Zhang, Jianqing Chen and Wei Cai

Energy, 2021, vol. 224, issue C

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.

Keywords: Eco-efficiency; Industrial production; Data driven; Emergy; Sustainability (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:224:y:2021:i:c:s0360544221004199

DOI: 10.1016/j.energy.2021.120170

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