Resumen:
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[EN] Recent practices in textile supply chains (SC) show a growing concern for sustainability not only in its economic
dimension, but fundamentally in its environmental and social ones. One of the key management processes ...[+]
[EN] Recent practices in textile supply chains (SC) show a growing concern for sustainability not only in its economic
dimension, but fundamentally in its environmental and social ones. One of the key management processes that
affect sustainability is the SC operations planning since its fundamental role in achieving a balance between
supply and demand in a sustainable manner. Moreover, in an uncertain and dynamic environment such as the
textile sector, it is necessary to provide a certain learning capability to the operations planning techniques used to
increase the speed and quality of response of the textile SC to unexpected situations. In this context, mathematical
programming models, heuristics and artificial intelligence techniques have proven their validity to
achieve sustainable, robust and smart supply chains. Despite their potential, neither a conceptual framework
(CF) nor a literature review have been detected to support the development and study of such models in the
textile supply chain operations planning. In view of these gaps, this paper proposes a CF for supporting the
sustainable and smart operations planning of the textile supply chains in a dynamic and uncertain context based
on a set of dimensions, categories and elements that reflect the specific characteristics of the textile sector.
Firstly, a tentative CF is predefined based on other generic works on SC operations planning in uncertain context
and the own authors¿ knowledge. Secondly, a structured literature review based on this CF has been made
resulting, at the same time, in the updating of some of its dimensions, categories and elements to reflect some
textile specific characteristics. Consequently, the CF is not only predefined but also logically derived from the
literature analysis. The results of the literature review show that there is a great opportunity to contribute to
making textile supply chains more sustainable, smart, flexible, robust and resilient in dynamic and uncertain
environments.
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Agradecimientos:
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This research was initiated in the framework of the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE) now closed. Then, it was further developed in the framework of the projects entitled "Industrial ...[+]
This research was initiated in the framework of the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE) now closed. Then, it was further developed in the framework of the projects entitled "Industrial Production and Logistics Optimization in Industry 4.0 (i4OPT) (PROMETEO/2021/065) " and "Autonomous And Self-Organized Artificial Intelligent Orchestrator For a Greener Industry 4.0" (TALON) (UE 101070181) . Leandro L. Lorente-Leyva and Diego H. Peluffo-Ordonez are greatly grateful by the support given by the SDAS Research Group (https://sdas-group.com /) . Funding for open access charge: CRUE-Universitat Politecnica de Valencia.
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