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Prognostic and health management (PHM) methods focus on improving the performance and reliability of systems with a high degree of complexity and criticality. These systems include engines, turbines, and robotic systems. PHM methods involve managing technical processes, such as condition monitoring, fault diagnosis, health prognosis, and maintenance decision-making. Various software and applications deal with the processes mentioned above independently. We can also observe different development levels, making connecting all of the machine’s technical processes in one health management system with the best possible output a challenging task. This study’s objective was to outline the scope of PHM methods in real-time conditions and propose new directions to develop a decision support tool for marine diesel engines. In this paper, we illustrate PHM processes and the state of the art in the marine industry for each technical process. Then, we review PHM methods and limitations for marine diesel engines. Finally, we analyze future research opportunities for the marine industry and their role in developing systems’ performance and reliability. The main added value of the research is that a research gap was found in this research field, which is that new advanced PHM methods have to be implemented for marine diesel engines. Our suggestions to improve marine diesel engines’ operation and maintenance include implementing advanced PHM methods and utilizing predictive analytics and machine learning.
Gharib et al. (Sat,) studied this question.