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Publication
Systematic review of predictive maintenance practices in the manufacturing sector
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| 2.72 MB | Adobe PDF |
Advisor(s)
Abstract(s)
Predictive maintenance (PDM) is emerging as a strong transformative tool within Industry 4.0, enabling
significant improvements in the sustainability and efficiency of manufacturing processes. This in-depth
literature review, which follows the PRISMA 2020 framework, examines how PDM is being implemented in
several areas of the manufacturing industry, focusing on how it is taking advantage of technological advances
such as artificial intelligence (AI) and the Internet of Things (IoT). The presented in-depth evaluation of
the technological principles, implementation methods, economic consequences, and operational improvements
based on academic and industrial sources and new innovations is performed. According to the studies,
integrating CDM can significantly increase machine uptime and reliability while reducing maintenance costs.
In addition, the transition to PDM systems that use real-time data to predict faults and plan maintenance
more accurately holds out promising prospects. However, there are still gaps in the overall methodologies for
measuring the return on investment of PDM implementations, suggesting an essential research direction.
Description
Keywords
Predictive maintenance Fault diagnosis systems Artificial intelligence in manufacturing Real-time monitoring
Citation
Benhanifia, Abdeldjalil; Ben Cheikh, Zied; Oliveira, Paulo Moura; Valente, Antonio; Lima, José (2025). Systematic review of predictive maintenance practices in the manufacturing sector. Intelligent Systems with Applications. ISSN 2667-3053. 26, p. 1-17
Publisher
Elsevier