Multi-objective optimization model for sustainable production planning in textile MSMEs

被引:0
作者
Flores-Siguenza P. [1 ]
Marmolejo-Saucedo J.A. [2 ]
Guamán R. [1 ]
机构
[1] Department of Applied Chemistry and Systems of Production, Faculty of Chemical Sciences, Universidad de Cuenca, Cuenca
[2] Facultad de Ingenieria, Universidad Nacional Autonoma de Mexico, Ciudad de Mexico
关键词
MSMEs; Multi-objective Optimization; Sustainable Production Planning; Textile Industry;
D O I
10.4108/eetinis.v10i3.3752
中图分类号
学科分类号
摘要
Textile micro, small and medium-sized enterprises (MSMEs) are characterized by their great influence on the economy of the countries, both for their contribution to the gross domestic product as well as for the generation of employment. In recent years, the complexity of their operations, instability and lack of balance between economic, environmental and social factors, axes of sustainable development, stand out. Therefore, it is necessary to implement approaches such as sustainable manufacturing and production planning, which seeks the creation of products with minimal environmental impact, under safe conditions for workers, and economically robust. In this context, this study aims to develop a multi-objective optimization model that enhances sustainable production planning in textile MSMEs. The methodology is based on two phases, the first one focused on the acquisition of information and the second one dedicated to the mathematical formulation of the model, where three objective functions focused on economic, environmental and social factors are proposed. The model is validated with real data from a textile MSME in Ecuador and different production alternatives are generated by proposing the implementation and use of photovoltaic energy as well as a greater use of personal protective equipment. One of the relevant outcomes of the study is a sustainable decision support tool aimed at the textile industry, where different scenarios for production planning and their respective economic, environmental and social consequences are shown. © 2023 Flores-Siguenza et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
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