Evaluation of green lean production in textile industry: a hybrid fuzzy decision-making framework

Vahabi Nejat, Shadi, Avakh Darestani, Soroush, Omidvari, Manouchehr and Amin Adibi, Mohammad Amin (2021) Evaluation of green lean production in textile industry: a hybrid fuzzy decision-making framework. Environmental Science and Pollution Research. ISSN 1614-7499 (In Press)

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Official URL: https://doi.org/10.1007/s11356-021-16211-4

Abstract / Description

Textile industry is an old and effective industry in Iran. However, due to its age and high energy consumption, this industry has low profitability and entrepreneurship. One of the most important problems of the weaving industry is the issue of waste regarding manpower, materials, machinery, and especially energy consumption. Another problem is environmental pollution. In this paper, using a multiple decision-making model for ranking and selecting criteria and sub-criteria, which is presented using the step-wise weight assessment ratio analysis (SWARA) and also by examining several industrial plants on weaving, the final ranking was performed using the fuzzy COPRAS method. According to the final result and using the opinions of experts and reviewing the studied cases, the environmental criterion was more important than other criteria, and also according to the existing sub-criteria, the amount of CO2 production and pH in the process of completion and washing and the types of pollution in the effluent and sewage were more important than other sub-criteria. Also, among the alternatives, company 5 is evaluated as the best alternative.

Item Type: Article
Uncontrolled Keywords: green; lean production; textile industry; fuzzy; decision-making techniques; evaluation framework
Subjects: 500 Natural Sciences and Mathematics > 580 Plants (Botany)
600 Technology > 620 Engineering & allied operations
600 Technology > 670 Manufacturing
Department: Guildhall School of Business and Law
Depositing User: Soroush Avakh Darestani
Date Deposited: 21 Sep 2021 07:48
Last Modified: 24 Aug 2022 01:58
URI: https://repository.londonmet.ac.uk/id/eprint/6987


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