Predictive Maintenance Approaches: A Systematic Literature Review
Open Access
- 11 November 2025
- conference paper
- Published by MDPI AG in Engineering Proceedings
- Vol. 112 (1) , 70
Abstract
Since increasing attention has been given to predictive maintenance (PdM) of industrial equipment, in order to enhance operational efficiency, improve reliability, and reduce downtime, this powerful strategy offers significant benefits, holds clearly great promises, and is now regarded as a key for future perspective in Industry 4.0. There are various approaches to PdM, each offering its own set of advantages and disadvantages which are single and hybrid approaches to carrying out diagnostics and prognostics in PdM. In this paper we will compare these approaches according to different aspects such as complexity of data and interpretability of results. Moreover, we also discuss the barriers to successful adoption, such as data quality, system complexity, and the need for workforce training. Finally, this paper concludes by identifying future research directions in response to scientific problems, which will drive the next wave of innovation in predictive maintenance solutions.Keywords
This publication has 42 references indexed in Scilit:
- An improved regularized particle filter for remaining useful life prediction in nuclear plant electric gate valvesNuclear Engineering and Technology, 2022
- A Decision-Based Framework for Predictive Maintenance Technique Selection in Industry 4.0Procedia CIRP, 2022
- Ontology-augmented Prognostics and Health Management for shopfloor-synchronised joint maintenance and production management decisionsJournal of Industrial Information Integration, 2022
- Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognosticsJournal of Manufacturing Systems, 2020
- A process-based automotive troubleshooting service and knowledge management system in collaborative environmentRobotics and Computer-Integrated Manufacturing, 2020
- A Framework for Automatic Generation of Augmented Reality Maintenance & Repair Instructions based on Convolutional Neural NetworksProcedia CIRP, 2020
- A predictive association rule-based maintenance policy to minimize the probability of breakages: application to an oil refineryThe International Journal of Advanced Manufacturing Technology, 2019
- Least squares support vector machine (LS-SVM)-based chiller fault diagnosis using fault indicative featuresApplied Thermal Engineering, 2019
- Real-time big data processing for anomaly detection: A SurveyInternational Journal of Information Management, 2019
- A hybrid ARIMA–SVM model for the study of the remaining useful life of aircraft enginesJournal of Computational and Applied Mathematics, 2019