Abstract
The main objective of this paper is to present a Remaining Useful Life (RUL) calculation approach, based on physical based simulation models, for the predictive maintenance of a production plant using Prognostics and health management (PHM) techniques. The resources of the production plant are modelled in order to enable the simulation of their functionalities. A smart control system is developed, aiming to gather machine data, both from the machine controller and the external sensors, before providing them as input to the simulation tool. The outcome of the simulation is the prediction of the machine's health status, which then is used for the identification of the machine's maintenance activities. Efficient algorithms and technologies for data analysis and prediction are utilized. In this way, the condition and the status of the machines can be predicted as a result from the simulation of physically-based models, without the machines' operation being stopped, as it happens in the common predictive maintenance solutions.
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