Most prognostics and health management publications focus on the development of algorithms to monitor and estimate the health condition of individual components. However, estimating the remaining useful life (RUL) of complex systems comprising multiple components is a more relevant topic for the industry. An accurate system-level RUL prediction can be used as a powerful decision support tool to help industry practitioners reduce operational costs and increase availability of systems. This paper presents a method to estimate the RUL of multiple-component systems based on health monitoring information regarding each component in the system under consideration. The proposed method relates the health factors of each component to its performance. Then, a system-level performance indicator is computed based on the performance of each component and a system architecture function that describes the relations among different components within the system. The system-level RUL is then estimated based on the extrapolation of the system-level performance indicator and a known failure threshold. In the proposed method, a system failure is not necessarily connected with a component failure. We present two case studies to illustrate the application of the proposed method: 1) a simplified aircraft hydraulic system containing multiple pumps; and 2) an aircraft air conditioning system containing different components.

Remaining useful life (RUL) estimations obtained from a prognostics and health monitoring (PHM) system can be used to plan in advance for the repair of components before a failure occurs. However, when system architecture is not taken into account, the use of PHM information may lead the operator to rush to replace a component that would not affect immediately the operation of the system under consideration. This paper presents a methodology for decision support in maintenance planning with application in aeronautical systems. The proposed methodology combines system architecture information and RUL estimations for all components in the system under study, allowing the estimation of an overall system-level RUL (S-RUL). The S-RUL information can be used to support maintenance decisions regarding the replacement of multiple components. For this purpose, the decision problem can be cast into an optimization framework involving the minimization of the component replacement cost under a safety constraint. Two case studies are used to illustrate the S-RUL concept, as well as the proposed optimization methodology.