Spare parts inventory classification using Neutrosophic Fuzzy EDAS method in the aviation industry

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dc.authoridCAKMAK, Emre/0000-0002-3406-3144
dc.authorwosidCAKMAK, Emre/HNQ-5290-2023
dc.contributor.authorCakmak, Emre
dc.contributor.authorGuney, Eda
dc.date.accessioned2024-05-19T14:42:51Z
dc.date.available2024-05-19T14:42:51Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractEvery physical asset and product that contributes to production or service is called inventory in the production or service industry. Inventories counted among companies' assets are important since they protect companies from various undesirable situations. Inventories often include large numbers, although they vary from company to company. Changes in the market affect the customer's procurement behavior. Inventories shaped by customers' demands are therefore seen as a source of uncertainty and cost for companies. The aviation industry is one of the most important transportation modes in the transportation industry and has the ability to transport faster than other industries. One of the vital issues in aviation businesses is the uninterrupted continuation of services. Accordingly, spare parts management is one of the issues that aviation companies attach importance to. Generally, spare parts management in most aviation companies aims to achieve a high customer service level with minimum inventory and minimum inventory investment. Aviation companies can achieve this goal through inventory classification. By using well-prepared inventory classification, these companies can reduce their inventory costs and classify their inventory to increase customer satisfaction and efficient production. This study aims to classify spare parts inventories by using the Neutrosophic Fuzzy EDAS method to achieve high inventory management efficiency in cases of inconsistent and uncertain information in the aviation industry. By adopting this recent multi-criteria decision-making method (MCDM), this study not only provides high inventory management efficiency but also determines required spare parts classification criteria for the aviation industry.en_US
dc.identifier.doi10.1016/j.eswa.2023.120008
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.scopus2-s2.0-85151743285en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org10.1016/j.eswa.2023.120008
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5292
dc.identifier.volume224en_US
dc.identifier.wosWOS:000981257300001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectInventory Classificationen_US
dc.subjectMulti-Criteria Spare Parts Classificationen_US
dc.subjectMulti-Criteria Decision-Makingen_US
dc.subjectNeutrosophic Fuzzy Edasen_US
dc.titleSpare parts inventory classification using Neutrosophic Fuzzy EDAS method in the aviation industryen_US
dc.typeArticleen_US

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