Application of MADM methods in Industry 4.0: A literature review

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dc.authoridDelen, Dursun/0000-0001-8857-5148
dc.authoridKilic, Huseyin Selcuk/0000-0003-3356-0162
dc.authoridZayat, Wael/0000-0002-9934-676X
dc.authorwosidYalçın, Ahmet Selçuk/ABB-8463-2020
dc.authorwosidzaim, selim/ABI-8229-2020
dc.authorwosidDelen, Dursun/AGA-9892-2022
dc.authorwosidKilic, Huseyin Selcuk/GSI-4768-2022
dc.contributor.authorZayat, Wael
dc.contributor.authorKilic, Huseyin Selcuk
dc.contributor.authorYalcin, Ahmet Selcuk
dc.contributor.authorZaim, Selim
dc.contributor.authorDelen, Dursun
dc.date.accessioned2024-05-19T14:45:52Z
dc.date.available2024-05-19T14:45:52Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractIndustry 4.0 has received inordinate attention from the business as well as research communities. Along with the development of Industry 4.0 applications and the diversity of potential alternatives, Multi-Attribute Decision Making (MADM) techniques have been employed by researchers as systematic approaches to support the decision-making processes. However, as the adoption of Industry 4.0 technologies requires considerable capital, and as it is relatively difficult to identify the suitable MADM method for the decision-making process in certain conditions, it becomes necessary to determine which components of Industry 4.0 are most commonly in demand of MADM applications of decision making, and which MADM techniques are mostly preferred by researchers and businesses for varied directions of Industry 4.0. Therefore, this study aims to provide a comprehensive review of MADM methods and their applications for different components of Industry 4.0. A methodology, including a review framework, is provided for the related analyses. The proposed framework includes analyses concerning methods, subtopics, and bibliometry along with the related exploratory tables and figures. Finally, the trends and research gaps are clearly stated to shed light on the further research areas taking into consideration different challenges that can be encountered by researchers, along with a set of propositions to potentially overcome them.en_US
dc.identifier.doi10.1016/j.cie.2023.109075
dc.identifier.issn0360-8352
dc.identifier.issn1879-0550
dc.identifier.scopus2-s2.0-85150784564en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org10.1016/j.cie.2023.109075
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5378
dc.identifier.volume177en_US
dc.identifier.wosWOS:000944706100001en_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.ispartofComputers & Industrial Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectMulti-Criteria Decision Making (Mcdm)en_US
dc.subjectMulti-Attribute Decision-Making (Madm)en_US
dc.subjectMulti-Objective Decision-Making (Modm)en_US
dc.subjectIndustry 4en_US
dc.subject0en_US
dc.subjectPrescriptive Analyticsen_US
dc.subjectDecision Supporten_US
dc.titleApplication of MADM methods in Industry 4.0: A literature reviewen_US
dc.typeReview Articleen_US

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