Selection of internet of things-enabled sustainable real-time monitoring strategies for manufacturing processes using a disc spherical fuzzy schweizer–sklar aggregation model

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dc.authorscopusidErfan Babaee Tirkolaee / 57196032874
dc.authorwosidErfan Babaee Tirkolaee / U-3676-2017
dc.contributor.authorAshraf, Shahzaib
dc.contributor.authorNaeem, Muhammad
dc.contributor.authorIqbal, Wania
dc.contributor.authorFarid, Hafiz Muhammad Athar
dc.contributor.authorShakeel, Hafiz Muhammad
dc.contributor.authorSimic, Vladimir
dc.contributor.authorTırkolaee, Erfan Babaee
dc.date.accessioned2025-04-17T11:46:27Z
dc.date.available2025-04-17T11:46:27Z
dc.date.issued2025
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümü
dc.description.abstractThe emergence of the Internet of Things (IoT) for monitoring in real-time is geared towards sustainable energy consumption practices by taking control over energy loss. The promising potential of current IoT real-time monitoring systems paves the way for future developments in monitoring devices with eco-friendly sensing capabilities. As a result, the creation of effective IoT real-time monitoring devices targeted at decreasing energy loss becomes crucial. This modeling procedure falls under the realm of multiple-attribute group decision-making (MAGDM), aiming to integrate the Schweizer-Sklar (SS) in-norm and in-conorm within the disc spherical fuzzy (D-SF) framework. The objective is to enhance the flexibility of D-SF in dealing with intricate and uncertain data. The core focus of this research is on deriving SS in-norm and in-conorm for D-SF data, consequently introducing innovative aggregation operators. The article offers the fundamental D-SF operations using SS aggregation operators in a systematic manner, with thorough theorem justifications. A new MAGDM tool is presented, created simply to manage ambiguous and imprecise data utilizing the suggested operators. Our model is specifically designed to tackle the critical issue of reducing energy loss in IoT real-time monitoring systems. The research not only focuses on model accuracy but also emphasizes its effectiveness in solving this pressing problem, demonstrating significant advancements in sustainable energy practices. Moreover, the proposed aggregation operators are subjected to a comparative analysis. This comprehensive comparison not only enhances the operators' efficacy but also underscores their relevance in real-world decision-making scenarios.
dc.description.sponsorshipDeanship for Research and Innovation Ministry of Education - Kingdom of Saudi Arabia
dc.identifier.citationAshraf, S., Naeem, M., Iqbal, W., Farid, H. M. A., Shakeel, H. M., Simic, V., & Tırkolaee, E. B. (2025). Selection of Internet of Things-enabled sustainable real-time monitoring strategies for manufacturing processes using a disc spherical fuzzy Schweizer–Sklar aggregation model. Engineering Applications of Artificial Intelligence, 139, 109607.
dc.identifier.doi10.1016/j.engappai.2024.109607
dc.identifier.endpage25
dc.identifier.issn09521976
dc.identifier.scopus2-s2.0-85209625631
dc.identifier.scopusqualityQ1
dc.identifier.startpage1
dc.identifier.urihttp://dx.doi.org/10.1016/j.engappai.2024.109607
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6231
dc.identifier.volume139
dc.identifier.wosWOS:001364277900001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorTırkolaee, Erfan Babaee
dc.institutionauthoridErfan Babaee Tirkolaee / 0000-0003-1664-9210
dc.language.isoen
dc.publisherElsevier ltd
dc.relation.ispartofEngineering applications of artificial intelligence
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectApplied Decision-Making
dc.subjectDisc Spherical Fuzzy Sets
dc.subjectInternet of Things
dc.subjectReal-Time Monitoring Systems
dc.subjectSchweizer–Sklar Prioritized Aggregation Operators
dc.titleSelection of internet of things-enabled sustainable real-time monitoring strategies for manufacturing processes using a disc spherical fuzzy schweizer–sklar aggregation model
dc.typeArticle

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