A data-driven scheduling framework to optimise aircraft line maintenance
| dc.contributor.author | Karadimas, Georgios | |
| dc.contributor.author | Pagone, Emanuele | |
| dc.contributor.author | Albakkoush, Salah Muftah M. | |
| dc.contributor.author | Salonitis, Konstantinos | |
| dc.date.accessioned | 2026-03-23T15:25:33Z | |
| dc.date.available | 2026-03-23T15:25:33Z | |
| dc.date.freetoread | 2026-03-23 | |
| dc.date.issued | 2025-10-17 | |
| dc.date.pubOnline | 2026-02-18 | |
| dc.description.abstract | Ensuring efficient and sustainable aircraft maintenance scheduling is critical for compliance, operational performance, and resource optimisation in Maintenance, Repair, and Overhaul (MRO) operations. This study presents a novel framework integrating mathematical modeling and discrete event simulations to optimise line maintenance scheduling. The Program Evaluation and Review Technique (PERT) is employed to model maintenance task durations, while Monte Carlo Simulations assess uncertainty and resource constraints, particularly tool availability. A case study using real-world data from a commercial MRO operator in Libya validates the framework, demonstrating its potential to reduce downtime, enhance resource utilisation, and improve sustainability in MRO operations. This research contributes to the development of data-driven maintenance strategies, addressing key challenges in airline MRO scheduling and supporting more efficient and resilient aviation maintenance practices. | |
| dc.description.conferencename | 13th CIRP Global Web Conference (CIRPe 2025) | |
| dc.description.journalName | Procedia CIRP | |
| dc.format.extent | pp. 251-255 | |
| dc.identifier.citation | Karadimas G, Pagone E, Albakkoush S, Salonitis K. (2026) A data-driven scheduling framework to optimise aircraft line maintenance. Procedia CIRP, Volume 139, 2026, pp. 251-255 | en_UK |
| dc.identifier.elementsID | 868988 | |
| dc.identifier.issn | 2212-8271 | |
| dc.identifier.uri | https://doi.org/10.1016/j.procir.2025.09.034 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/25009 | |
| dc.identifier.volumeNo | 139 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | en_UK |
| dc.publisher.uri | https://www.sciencedirect.com/science/article/pii/S2212827125009989?via%3Dihub | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | 40 Engineering | en_UK |
| dc.subject | 4014 Manufacturing engineering | en_UK |
| dc.subject | Aircraft maintenance | en_UK |
| dc.subject | Maintenance | en_UK |
| dc.subject | Repair | en_UK |
| dc.subject | Overhaul (MRO) scheduling | en_UK |
| dc.subject | Program Evaluation | en_UK |
| dc.subject | Review Technique (PERT) | en_UK |
| dc.subject | Monte Carlo Simulation (MCS) | en_UK |
| dc.subject | Discrete Event Simulation (DES) | en_UK |
| dc.subject | Sustainability in aviation | en_UK |
| dc.title | A data-driven scheduling framework to optimise aircraft line maintenance | en_UK |
| dc.type | Article | |
| dcterms.temporal.endDate | 17-OCT-2025 | |
| dcterms.temporal.startDate | 16-OCT-2025 |
