H2020-REMAP – Real-time Condition-based Maintenance for Adaptive Aircraft Maintenance Planning
Description
ReMAP will develop an Integrated Fleet Health Management (IFHM) solution to demonstrate cost and safety benefits, propose standards, and support the certification of CBM for aircraft structure and systems, paving the way for the implementation of CBM in the European air transport system. To fulfil this objective, the following set of specific technical goals are defined: - develop an integrated approach for CBM, combining structures and systems health monitoring; - explore and optimize the use of different sensing technologies for structural health management (SHM); - develop an open IT ecosystem of cloud services, supported by an IT platform, to enable fast processing and analysis of data from several sensors, to support data analytics, and enable real-time decision support, reacting to just-in-time data as soon as it is made available via satellite or very high frequency (VHF) radio transmission when the aircraft is flying or via Wi-Fi or 3G/4G when the aircraft lands; - develop data-driven probabilistic algorithms for aerostructures damage monitoring (diagnosis) and remaining useful life (RUL) estimation (prognosis), with uncertainty quantification; - develop a hybrid approach, combining machine-learning based data analytics algorithms and physics based models, for diagnostics, prognostics and health management (PHM) of dissimilar aircraft systems; - develop lean algorithms for on-board data processing and pre-diagnoses for critical aircraft systems, using an edge computing approach - develop an efficient maintenance packaging and schedule optimisation algorithm for real-time adaptive fleet maintenance management based on continuous structures and systems health assessment; - develop a quantitative safety risk assessment methodology for CBM; - improve root cause analysis of failures, to facilitate better future structures and systems design.Researchers
Bernardete Ribeiro (coordinator)
Penousal Machado
António Dourado
Catarina Silva
Alberto Cardoso
Licínio Roque
Joel P. Arrais
Penousal Machado
António Dourado
Catarina Silva
Alberto Cardoso
Licínio Roque
Joel P. Arrais
Partners
TUDelft, Atos Spain, Cedrat Technologies, ParisTech Arts Et Métiers, Embraer, IPN, KLM, Onera French Aerospace Lab, Optimal, Smartec, UTRCI United Technologies Research Center Ireland, University of PatrasTotal budget
6 800 000,00 €Local budget
291 000,00 €Keywords
Condition-Based Monitoring, Machine Learning, Cloud Computing, Information Systems PlatformStart Date
2018-06-01End Date
2022-06-01Journal Articles
Conference Articles
2019
(2 publications)- Azevedo, D. and Ribeiro, B. and Alberto Cardoso , "Web-based tool for predicting the Remaining Useful Lifetime of Aircraft Components", in 2019 5th Experiment International Conference (exp.at'19), 2019
- Azevedo, D. and Ribeiro, B. and Alberto Cardoso , "Online Simulation of Methods to Predict the Remaining Useful Lifetime of Aircraft Components", in 2019 5th Experiment International Conference (exp.at'19), 2019