Analyzing Emerging Challenges for Data-Driven Predictive Aircraft Maintenance Using Agent-Based Modeling and Hazard Identification

The increasing use of on-board sensor monitoring and data-driven algorithms has stimulated the recent shift to data-driven predictive maintenance for aircraft. This paper discusses emerging challenges for data-driven predictive aircraft maintenance. We identify new hazards associated with the introduction of data-driven technologies into...

Designing reliable, data-driven maintenance for aircraft systems with applications to the aircraft landing gear brakes

When designing the maintenance of multi-component aircraft systems, we consider parameters such as safety margins (used when component replacements are scheduled), and reliability thresholds (used to define data-driven Remaining-Useful-Life prognostics of components). We propose Gaussian process learning and novel adaptive sampling techniques to...

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...

Remaining-Useful-Life prognostics for opportunistic grouping of maintenance of landing gear brakes for a fleet of aircraft

Several studies have proposed Remaining-Useful-Life (RUL) prognostics for aircraft components in the last years. However, few studies focus on integrating these RUL prognostics into maintenance planning frameworks. This paper proposes an optimization model for opportunistic maintenance scheduling of aircraft components that integrates RUL...

Multi-objective design of aircraft maintenance using Gaussian process learning and adaptive sampling

Aircraft maintenance design aims to identify strategies that render the aircraft reliable for flight in a cost-efficient manner. These are often conflicting objectives. Moreover, existing studies on maintenance design often limit themselves to only one type of maintenance strategy, overlooking other potentially dominating designs. We propose...

Predictive Aircraft Maintenance: Modeling and Analysis Using Stochastic Petri Nets

Predictive aircraft maintenance is a complex process, which requires the modeling of the stochastic degradation of aircraft systems, as well as the dynamic interactions between the stakeholders involved. In this paper, we show that the stochastically and dynamically colored Petri nets (SDCPNs) are able to formalize the predictive aircraft...

Multi-objective Analysis of Condition-based Aircraft Maintenance Strategies using Discrete Event Simulation

As aircraft maintenance is transitioning towards data- driven condition-based maintenance (CBM), its cost and performance objectives need to be re-evaluated: how are these objectives related under various CBM strategies?; which objectives are conflicting?; what are the trade-offs between the conflicting objectives?; what is the impact of this...

An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets

Aircraft maintenance is key for safe and efficient aircraft operations. While most studies propose cost-efficient maintenance strategies, the safety and efficiency of these strategies need to be quantified. This paper proposes a formal framework to assess the safety and efficiency of maintenance strategies by means of agent-based modelling,...