Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS

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dc.contributor.authorMenekşe, Akın
dc.contributor.authorErtemel, Adnan Veysel
dc.contributor.authorAkdağ Camgöz, Hatice
dc.contributor.authorGörener, Ali
dc.date.accessioned2023-05-11T11:56:04Z
dc.date.available2023-05-11T11:56:04Z
dc.date.issued2023en_US
dc.departmentFakülteler, İşletme Fakültesi, İşletme Bölümüen_US
dc.description.abstractFor many different types of businesses, additive manufacturing has great potential for new product and process development in many different types of businesses including automotive industry. On the other hand, there are a variety of additive manufacturing alternatives available today, each with its own unique characteristics, and selecting the most suitable one has become a necessity for relevant bodies. The evaluation of additive manufacturing alternatives can be viewed as an uncertain multi-criteria decision-making (MCDM) problem due to the potential number of criteria and candidates as well as the inherent subjectivity of various decision-experts engaging in the process. Pythagorean fuzzy sets are an extension of intuitionistic fuzzy sets that are effective in handling ambiguity and uncertainty in decision-making. This study offers an integrated fuzzy MCDM approach based on Pythagorean fuzzy sets for assessing additive manufacturing alternatives for the automotive industry. Objective significance levels of criteria are determined using the Criteria Importance Through Inter-criteria Correlation (CRITIC) technique, and additive manufacturing alternatives are prioritized using the Evaluation based on Distance from Average Solution (EDAS) method. A sensitivity analysis is performed to examine the variations against varying criterion and decision-maker weights. Moreover, a comparative analysis is conducted to validate the acquired findings.en_US
dc.identifier.doi10.1371/journal.pone.0282676en_US
dc.identifier.issue3en_US
dc.identifier.pmid36893100en_US
dc.identifier.scopus2-s2.0-85149659295en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11467/6608
dc.identifier.urihttps://doi.org/10.1371/journal.pone.0282676
dc.identifier.volume18en_US
dc.identifier.wosWOS:000949067800063en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.ispartofPLoS ONEen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleAdditive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDASen_US
dc.typeArticleen_US

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