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

J. Lee; M.A. Mitici; S. Geng; M. Yang

doi:10.3850/978-981-18-5183-4_R01-04-288-cd

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

J. Lee^*, M.A. Mitici, S. Geng, M. Yang

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

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 efficiently optimize these design parameters. We illustrate our approach for aircraft landing gear bakes. Data-driven, Remaining-Useful-Life prognostics for brakes are obtained using a Bayesian linear regression. Pareto optimal safety margins for scheduling brake replacements are identified, together with Pareto optimal reliability thresholds for prognostics.

Original language	English
Title of host publication	Proceedings of the 32nd European Safety and Reliability Conference
Editors	Maria Chiara Leva, Edoardo Patelli, Luca Podofillini, Simon Wilson
Publisher	ESREL
Pages	25-35
Number of pages	11
ISBN (Print)	9789811851834
DOIs	https://doi.org/10.3850/978-981-18-5183-4_R01-04-288-cd
Publication status	Published - 2022
Event	32nd European Safety and Reliability Conference (ESREL 2022) - Dublin, Ireland Duration: 28 Aug 2022 → 1 Sept 2022 Conference number: 32 https://www.esrel2022.com/

Publication series

Name	Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future

Conference

Conference	32nd European Safety and Reliability Conference (ESREL 2022)
Abbreviated title	ESREL 2022
Country/Territory	Ireland
City	Dublin
Period	28/08/22 → 1/09/22
Internet address	https://www.esrel2022.com/

Access to Document

10.3850/978-981-18-5183-4_R01-04-288-cd

Designing-reliable-data-driven-maintenance-for-aircraft-systemsFinal published version, 364 KB

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Lee, J., Mitici, M. A., Geng, S., & Yang, M. (2022). Designing reliable, data-driven maintenance for aircraft systems with applications to the aircraft landing gear brakes. In M. C. Leva, E. Patelli, L. Podofillini, & S. Wilson (Eds.), Proceedings of the 32nd European Safety and Reliability Conference (pp. 25-35). (Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future). ESREL. https://doi.org/10.3850/978-981-18-5183-4_R01-04-288-cd

Lee, J. ; Mitici, M.A. ; Geng, S. et al. / Designing reliable, data-driven maintenance for aircraft systems with applications to the aircraft landing gear brakes. Proceedings of the 32nd European Safety and Reliability Conference. editor / Maria Chiara Leva ; Edoardo Patelli ; Luca Podofillini ; Simon Wilson. ESREL, 2022. pp. 25-35 (Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future).

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

abstract = "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 efficiently optimize these design parameters. We illustrate our approach for aircraft landing gear bakes. Data-driven, Remaining-Useful-Life prognostics for brakes are obtained using a Bayesian linear regression. Pareto optimal safety margins for scheduling brake replacements are identified, together with Pareto optimal reliability thresholds for prognostics.",

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booktitle = "Proceedings of the 32nd European Safety and Reliability Conference",

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Lee, J, Mitici, MA, Geng, S & Yang, M 2022, Designing reliable, data-driven maintenance for aircraft systems with applications to the aircraft landing gear brakes. in MC Leva, E Patelli, L Podofillini & S Wilson (eds), Proceedings of the 32nd European Safety and Reliability Conference. Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future, ESREL, pp. 25-35, 32nd European Safety and Reliability Conference (ESREL 2022), Dublin, Ireland, 28/08/22. https://doi.org/10.3850/978-981-18-5183-4_R01-04-288-cd

Designing reliable, data-driven maintenance for aircraft systems with applications to the aircraft landing gear brakes. / Lee, J.; Mitici, M.A.; Geng, S. et al.
Proceedings of the 32nd European Safety and Reliability Conference. ed. / Maria Chiara Leva; Edoardo Patelli; Luca Podofillini; Simon Wilson. ESREL, 2022. p. 25-35 (Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AB - 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 efficiently optimize these design parameters. We illustrate our approach for aircraft landing gear bakes. Data-driven, Remaining-Useful-Life prognostics for brakes are obtained using a Bayesian linear regression. Pareto optimal safety margins for scheduling brake replacements are identified, together with Pareto optimal reliability thresholds for prognostics.

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Lee J, Mitici MA, Geng S, Yang M. Designing reliable, data-driven maintenance for aircraft systems with applications to the aircraft landing gear brakes. In Leva MC, Patelli E, Podofillini L, Wilson S, editors, Proceedings of the 32nd European Safety and Reliability Conference. ESREL. 2022. p. 25-35. (Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future). doi: 10.3850/978-981-18-5183-4_R01-04-288-cd

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

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Predictive Aircraft Maintenance: Integrating Remaining-Useful-Life Prognostics into Maintenance Optimization

ReMAP: Real-time Condition-based Maintenance for Adaptive Aircraft Maintenance Planning

Innovation in Transport Applications, European Safety and Reliability Conference

Cite this

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

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Research output

Predictive Aircraft Maintenance: Integrating Remaining-Useful-Life Prognostics into Maintenance Optimization

Projects

ReMAP: Real-time Condition-based Maintenance for Adaptive Aircraft Maintenance Planning

Prizes

Innovation in Transport Applications, European Safety and Reliability Conference

Cite this