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Harnessing the Fourth Industrial Revolution: Trends and Challenges in Applying Industry 4.0 to Enhance Predictive Maintenance in Manufacturing, Specifically Mining

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dc.citedby0
dc.contributor.authorAlqaraleh D.A.en_US
dc.contributor.authorHajjaj S.en_US
dc.contributor.authorMohamed H.en_US
dc.contributor.authorid59453631900en_US
dc.contributor.authorid55812832600en_US
dc.contributor.authorid57136356100en_US
dc.date.accessioned2025-03-03T07:45:32Z
dc.date.available2025-03-03T07:45:32Z
dc.date.issued2024
dc.description.abstractThe combination of advanced technologies and data-driven decision-making in the Fourth Industrial Revolution presents substantial opportunities for improving manufacturing processes, particularly in the realm of predictive maintenance. Nevertheless, the utilization of this technology in the mining industry has not been thoroughly investigated. This research investigates the effects of Industry 4.0 on the practice of predictive maintenance within the manufacturing sector, with a specific emphasis on the mining industry. This study examines the various patterns and challenges associated with the implementation process, thereby addressing a gap in the existing literature. This research investigates the potential of Industry 4.0 in enhancing predictive maintenance within the manufacturing sector, with a specific focus on the mining industry. The study utilizes a content-centric methodology to examine the field of sustainable manufacturing, with a particular emphasis on identifying and evaluating promising technologies such as cyber-physical systems, the Internet of Things (IoT), big data analytics, digital twins, augmented reality (AR), and artificial intelligence (AI). Nevertheless, it is imperative to acknowledge and tackle various challenges that arise during the deployment of technology, such as security concerns, human factors, and the need for procedural enhancements. ? The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-3-031-70684-4_5
dc.identifier.epage74
dc.identifier.scopus2-s2.0-85210883720
dc.identifier.spage53
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85210883720&doi=10.1007%2f978-3-031-70684-4_5&partnerID=40&md5=46a830d4e74c56188e96c81956142dc7
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36891
dc.identifier.volume1132 LNNS
dc.pagecount21
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleLecture Notes in Networks and Systems
dc.subjectIndustry 4.0
dc.subjectMining industry
dc.subjectSmart manufacturing
dc.subjectAdvanced technology
dc.subjectData driven decision
dc.subjectDecisions makings
dc.subjectImplementation process
dc.subjectIndustrial revolutions
dc.subjectManufacturing industries
dc.subjectManufacturing process
dc.subjectManufacturing sector
dc.subjectMining sector
dc.subjectPredictive maintenance
dc.subjectPredictive maintenance
dc.titleHarnessing the Fourth Industrial Revolution: Trends and Challenges in Applying Industry 4.0 to Enhance Predictive Maintenance in Manufacturing, Specifically Miningen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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