Publication | Closed Access
Challenges to IoT-Enabled Predictive Maintenance for Industry 4.0
281
Citations
104
References
2019
Year
Web Of ThingEngineeringIndustrial EngineeringSmart CityIndustrial IotIntelligent SystemsIot SystemCurrent Pdm IssuesSystems EngineeringInternet Of ThingsIndustry 4.0Industrial InformaticsComputer EngineeringIot Data ManagementIot Data AnalyticsPredictive MaintenanceAutomationTechnologyDynamic Maintenance Paradigm
The Industry 4.0 paradigm is boosting the relevance of predictive maintenance (PdM) for manufacturing and production industries. PdM strongly relies on Internet of Things (IoT), which digitalizes the physical actions allowing human-to-human, human-to-machine, and machine-to-machine connections for intelligent perception. Several issues still need to be addressed for reaching the maturity stage for the widespread application of PdM. To do this, IoT needs to be empowered with data science capabilities, to reach the ultimate objective of digitalization, which is supporting decision making to optimally act on the physical systems. In this article, we present a comprehensive outlook of the current PdM issues, with the final aim of providing a deeper understanding of the limitations and strengths, challenges and opportunities of this dynamic maintenance paradigm. This is done through extensive research and analysis of the scientific and technical literature. On this basis, this article outlines some main research issues to be addressed for the successful development and deployment of IoT-enabled PdM in industry.
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