Abstract
With the rapid progress of network technologies and sensors, monitoring the sensor data such as pressure, temperature, current, vibration and other electrical, mechanical and chemical variables has become much more significant. With the arrival of Big Data and artificial intelligence (AI), sophisticated solutions can be developed to prevent failures and predict the equipment’s remaining useful life (RUL). These techniques allow for taking maintenance actions with haste and precision. Accordingly, this study provides a systematic literature review (SLR) of the predictive maintenance (PdM) techniques in transportation systems. The main focus of this study is the literature covering PdM in the motor vehicles’ industry in the last 5 years. A total of 52 studies were included in the SLR and examined in detail within the scope of our research questions. We provided a summary on statistical, stochastic and AI approaches for PdM applications and their goals, methods, findings, challenges and opportunities. In addition, this study encourages future research by indicating the areas that have not yet been studied in the PdM literature.
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
Reference97 articles.
1. Predictive maintenance in the Industry 4.0: A systematic literature review;Comput. Ind. Eng.,2020
2. Benabbou, L., Malki, Z., Sankaran, K., and Bouzekri, H. (2019, January 10–15). Machine Learning-based Predictive Maintenance for Renewable Energy: The Case of Power Plants in Morocco. Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, USA.
3. Keartland, S. (2020, January 29–31). Automating predictive maintenance using oil analysis and machine learning. Proceedings of the 2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa.
4. Mallouk, I., Sallez, Y., and El Majd, B.A. (2021, January 27–28). Machine learning approach for predictive maintenance of transport systems. Proceedings of the 2021 3rd International Conference on Transportation and Smart Technologies, Tangier, Morocco.
5. Wudhikarn, R. (2011, January 6–9). Implementation of Overall Equipment Effectiveness in Wire Mesh Manufacturing. Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, Singapore.
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