Supply chain sustainability improvement using exergy analysis
Computers & Industrial Engineering, ISSN: 0360-8352, Vol: 154, Page: 107142
2021
- 27Citations
- 96Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Sustainable supply chain management (SSCM) is an improved version of supply chain management, in which, not only economic issues but also social and environmental issues are considered. It can be achieved through extended exergy analysis which is a powerful thermodynamic tool for evaluating the sustainability of an industrial system. This paper provides an exergetic analysis to model and calculate the consumed exergy for sustainable supply chains. The model considers different objectives of financial, social and environmental aspects on selecting the more sustainable supply chain to produce and distribute productions. The proposed model is solved using a hybrid global- and local-search metaheuristic algorithm based on genetic algorithm and simulated annealing (named GLGASA). By minimizing the exergy cost, the authors provide an insight about the potential of the environmental destruction saving per unit of additional cost. This quantification of the cost and saving would be needed at the time of business case calculation for the new projects or modification and upgrade of the existing processes to achieve a better decision that guarantees both return of the investment and environmental protection. In order to validate the proposed methodology, a real food supply chain is presented and discussed to show the usability of the model and claim the benefits over the previously available models. According to the obtained results, the proposed method provides 4.48% saving in the consumed exergy of the supply chain by accepting additional economic costs.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0360835221000462; http://dx.doi.org/10.1016/j.cie.2021.107142; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85100667025&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0360835221000462; https://dx.doi.org/10.1016/j.cie.2021.107142
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know