articleResults in EngineeringSep 23, 2024GOLD OA

Paradigm shift for predictive maintenance and condition monitoring from Industry 4.0 to Industry 5.0: A systematic review, challenges and case study

AAAitzaz Ahmed MurtazaASAmina SaherMHMuhammad Hamza ZafarSKSyed Kumayl Raza MoosaviMFMuhammad Faisal Aftab

Capital University of Science and Technology · National University of Technology · +3 more institutions

Indexed incrossrefdoaj

Abstract

This paper examines the integration of Industry 5.0 principles with advanced predictive maintenance (PdM) and condition monitoring (CM) practices, based on Industry 4.0's enabling technologies. It provides a comprehensive review of the roles of Machine Learning (ML), Digital Twins (DT), the Internet of Things (IoT), and Big Data (BD) in transforming PdM and CM. The study proposes a six-layered framework designed to enhance sustainability, human-centricity, and resilience in industrial systems. This framework includes layers for data acquisition, processing, human-machine interfaces, maintenance execution, feedback, and resilience. A case study on a boiler feed-water pump is also presented which demonstrates…

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138
total citations
FWCI
125.80
Percentile
100%
References
215
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Authors

6

Topics & keywords

Topics
Keywords
  • Paradigm shift
  • Predictive maintenance
  • Industry 4.0
  • Business
  • Risk analysis (engineering)
  • Engineering
  • Computer science
  • Data mining
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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