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Emergy based intelligent decision-making model for remanufacturing process scheme integrating economic and environmental factors.

Authors :
Zhang, Xugang
Xu, Lu
Zhang, Hua
Jiang, Zhigang
Cai, Wei
Source :
Journal of Cleaner Production. Apr2021, Vol. 291, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

Remanufacturing has been recognized as a burgeoning technology with high economic benefits and low resource consumption. Remanufacturing process scheme planning is a key part of remanufacturing systems. However, the evaluation of the remanufacturing scheme involves many factors that are difficult to quantify, and the traditional Multiple Criteria Decision Making (MCDM) method mainly relies on setting subjective weights between criteria to complete the assessment, which reduces the objectivity and accuracy of the results. Therefore, a novel emergy based intelligent decision-making model is established to deal with these problems. Firstly, the goal, framework, and boundary of the intelligent decision-making model are defined and constructed. Then, an emergy mathematical model considering material, social cost, quality loss, time loss, waste treatment cost, and industrial waste is constructed, and the mechanism of emergy transfer and conversion is revealed. Besides, several evaluation indicators are proposed to comprehensively estimate the economic and environmental performance of the remanufacturing process scheme, which comprised Ecological Performance Indicator (E P I), Economic Benefit Indicator (E B I), and Environmentally Friendly Indicator (E F I). Finally, the feasibility and the effectiveness of the emergy based intelligent decision-making model are proved by the assessment of the case analysis of machine tool remanufacturing. The research results can provide suggestions for policymakers and enterprises to formulate management strategies and development plans. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09596526
Volume :
291
Database :
Academic Search Index
Journal :
Journal of Cleaner Production
Publication Type :
Academic Journal
Accession number :
148987189
Full Text :
https://doi.org/10.1016/j.jclepro.2020.125247