Towards online data-driven prognostics system

Complex engineering systems are always working in harsh operating conditions. Internal wears and tears of such systems can lead to catastrophic failures which affect system operation and endanger human lives in many cases. To avoid sudden failures, continuous monitoring, fault diagnosis, and failure prognosis are required. Prognostics as a discipline plays the major rule in impending failure prevention. Offline prognostics system focuses on maintenance and logistics operations whereas online prognostics focuses on maintaining safe operation. In a previous work we successfully developed an offline prognostics system for aircraft turbofan engines’ remaining useful life (RUL) estimation. In this paper we will show how we used the offline prognostics system as the baseline definition towards creating an online data-driven prognostics system to enable informed real-time decisions.