Proposal of Metrics to Visualise Performance of Prognostics Case Studies in Aerospace

With the increasing availability of sensor data to monitor the health of systems and components, maintenance is encountering a shift from the traditional preventive and corrective methodologies to a predictive approach. Given that maintenance, repair and overhaul are a significant operational cost to organizations, it is imperative that the...

Adaptations for CNN-LSTM Network for Remaining Useful Life Prediction: Adaptable Time Window and Sub-Network Training

Estimating the RUL (Remaining Useful Life) of machinery is a useful tool for maintenance and performance operations. This results in lower costs, improved safety and operational improvements.<br/>This paper proposes two adaptations to the CNN-LSTM network provided by Li et al. \cite{Li2019APrediction}, as well as exploring reproducibility,...

Prognostics-driven supply chain optimization in commercial aviation

Maintenance providers in commercial aviation are looking into new strategies to improve maintenance operations and aircraft availability in order to reduce cost and increase customer satisfaction. Aircraft availability and thus profitability highly relies on adequate maintenance because an aircraft is only profitable when...

Machine Learning for Predictive Maintenance: A Boeing 747 Bleed Air Valves case study

The newest generation of aircraft has seen a strong increase in sensor data generated on-board. The available data has the potential to indicate the health state of individual components based on which their maintenance requirements can be determined, a maintenance strategy called Condition Based Maintenance. Predictive Maintenance is a specific...