A resilience assessment framework for complex engineered systems using graphical evaluation and review technique (GERT)

System resilience characterizes the capability of maintaining the required functionality under disruptions, which is of great significance in evaluating the productivity and safety of complex engineered systems. Although most studies conduct resilience assessment from qualitative and quantitative perspectives, system functionality that reflects...

Predictive Maintenance Planning Using Renewal Reward Processes and Probabilistic RUL Prognostics: Analyzing the Influence of Accuracy and Sharpness of Prognostics

We pose the maintenance planning for systems using probabilistic Remaining Useful Life (RUL) prognostics as a renewal reward process. Data-driven probabilistic RUL prognostics are obtained using a Convolutional Neural Network with Monte Carlo dropout. The maintenance planning model is illustrated for aircraft turbofan engines. The results show...

Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics: The case of turbofan engines

The increasing availability of condition-monitoring data for components/systems has incentivized the development of data-driven Remaining Useful Life (RUL) prognostics in the past years. However, most studies focus on point RUL prognostics, with limited insights into the uncertainty associated with these estimates. This limits the...

Alarm-based predictive maintenance scheduling for aircraft engines with imperfect Remaining Useful Life prognostics

The increasing availability of condition monitoring data for aircraft components has incentivized the development of Remaining Useful Life (RUL) prognostics in the past years. However, only few studies consider the integration of such prognostics into maintenance planning. In this paper we propose a dynamic, predictive maintenance scheduling...

Deep reinforcement learning for predictive aircraft maintenance using probabilistic Remaining-Useful-Life prognostics

The increasing availability of sensor monitoring data has stimulated the development of Remaining-Useful-Life (RUL) prognostics and maintenance planning models. However, existing studies focus either on RUL prognostics only, or propose maintenance planning based on simple assumptions about degradation trends. We propose a framework to integrate...