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A Fuzzy Multicriteria Decision-Making Approach for Assessing the Preparedness Level for the Implementation of Logistics 4.0: A Case Study in the Food Industry

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 14056 LNCS, Page: 32-46
2023
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Conference Paper Description

Industries must prepare diagnoses that indicate their actual state in using Industry 4.0 technologies, especially in Logistics 4.0. So then, focused on the food sector industries, designing and testing a model to carry out this diagnosis is necessary. This project aims to present a Diagnostic and Characterization Model for the Food Sector Industries of the city of Barranquilla based on multifactorial strategies that help them evaluate and make decisions to increase the possibilities of implementing and adopting technologies established under the Logistics 4.0 in your supply chain. In this context, designing and testing a Diagnostic and Characterization Model for the Food Sector Industries will be carried out, applying a multicriteria methodology as AHP-TOPSIS and thus generating a tool that allows its applicability in the medium and long term.

Bibliographic Details

Genett Jimenez-Delgado; Monica Ardila-Parra; Gilberto Santos; José Carlos Sá; Vanda Lima; Leonardo Campis-Freyle; Lesvia Valero; Hugo Hernandez; Dionicio Neira-Rodado; Jannys Hernández-Ureche

Springer Science and Business Media LLC

Mathematics; Computer Science

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