TY - GEN
T1 - Criticality-based Predictive Maintenance Scheduling for Aircraft Components with a Limited Stock of Spare Components
AU - de Pater, I.I.
AU - Carrillo Galera, M.D.M.
AU - Mitici, M.A.
PY - 2021
Y1 - 2021
N2 - We propose a criticality-based scheduling model for aircraft component replacements.We schedule maintenance for a fleet of aircraft, each equipped with a multi-component system. The maintenance schedule takes into account a limited stock of spare components and the Remaining-Useful-Life prognostics for the components. We propose a component replacement scheduling model with three stages of maintenance criticality: i) critical aircraft that are not airworthy due to a lack of sufficient operational components, ii) predictive alerts for expected component failures, and iii) non-critical aircraft with some failed components. An Adaptive Large Neighborhood Search (ALNS) algorithm is developed to solve this criticality-based aircraft maintenance planning problem. The framework is illustrated for a fleet of aircraft, each equipped with a k-out-of-N system of components. A predictive maintenance planning is obtained within an outstanding computational time (less than 6 seconds for a fleet of 50 aircraft). Moreover, it is shown that the proposed planning with 3-levels of criticality ensures aircraft airworthiness while making cost-efficient use of maintenance slots.
AB - We propose a criticality-based scheduling model for aircraft component replacements.We schedule maintenance for a fleet of aircraft, each equipped with a multi-component system. The maintenance schedule takes into account a limited stock of spare components and the Remaining-Useful-Life prognostics for the components. We propose a component replacement scheduling model with three stages of maintenance criticality: i) critical aircraft that are not airworthy due to a lack of sufficient operational components, ii) predictive alerts for expected component failures, and iii) non-critical aircraft with some failed components. An Adaptive Large Neighborhood Search (ALNS) algorithm is developed to solve this criticality-based aircraft maintenance planning problem. The framework is illustrated for a fleet of aircraft, each equipped with a k-out-of-N system of components. A predictive maintenance planning is obtained within an outstanding computational time (less than 6 seconds for a fleet of 50 aircraft). Moreover, it is shown that the proposed planning with 3-levels of criticality ensures aircraft airworthiness while making cost-efficient use of maintenance slots.
KW - Predictive Aircraft Maintenance
KW - Spare Components Management
KW - Maintenance criticality
UR - http://www.scopus.com/inward/record.url?scp=85135458311&partnerID=8YFLogxK
U2 - 10.3850/978-981-18-2016-8_074-cd
DO - 10.3850/978-981-18-2016-8_074-cd
M3 - Conference contribution
SN - 9789811820168
T3 - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
SP - 55
EP - 62
BT - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
A2 - Castanier, Bruno
A2 - Cepin, Marko
A2 - Bigaud, David
A2 - Berenguer, Christophe
T2 - 31st European Safety and Reliability Conference
Y2 - 19 September 2021 through 23 September 2021
ER -