Citation:
Zakwan Skaf. Prognostics: Design, Implementation, and Challenges. 12th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, 9-11 June 2015, Oxford, UK.
Abstract:
Prognostics is an essential part of condition-based maintenance (CBM), described as predicting the remaining useful life
(RUL) of a system. It is also a key technology for an integrated vehicle health management (IVHM) system that leads
to improved safety and reliability. A vast amount of research has been presented in the literature to develop prognostics
models that are able to predict a system’s RUL. These models can be broadly categorised into experience-based models,
data-driven models and physics-based models. Therefore, careful consideration needs to be given to selecting which
prognostics model to take forward and apply for each real application. Currently, developing reliable prognostics models
in real life is challenging for various reasons, such as the design complexity associated with a system, the high uncertainty
and its propagation in the degradation, system level prognostics, the evaluation framework and a lack of prognostics
standards. This paper is written with the aim to bring forth the challenges and opportunities for developing prognostics
models for complex systems and making researchers aware of these challenges and opportunities.