A copula-based quantified airworthiness modelling for civil aircraft engines

Zhou, H. , Parlikad, A. K., Brintrup, A. and Harrison, A. (2023) A copula-based quantified airworthiness modelling for civil aircraft engines. Probabilistic Engineering Mechanics, 73, 103481. (doi: 10.1016/j.probengmech.2023.103481)

Abstract

The aircraft engine serves as the core system of an aircraft and operates under extreme conditions, requiring high reliability and absolute safety. The design, manufacturing, and after-sales services of aircraft engines are complex processes. To ensure safety and performance, maintenance checks are performed periodically and hierarchically throughout the engine’s life-cycle. Among these checks, shop visit (SV) heavy maintenance checks play a crucial role but are also costly, especially when they occur unexpectedly and unplanned. Analysis of the maintenance logbook, recording aviation operations, reveals a significant occurrence of unplanned SVs, which may be attributed to the existing maintenance policy based on a single time-definition. To address this issue, this paper seeks to establish a novel approach to quantifying airworthiness through copula modeling, which combines two time-definitions: the flying hour (FH) and the flying cycle (FC). This approach is unique in the aviation industry. By employing the Gumbel copula with the generalized extreme value (GEV) distribution as the marginal distribution, and utilizing non-parametric association measurement parameter estimation, the quantified airworthiness of civil aircraft engine fleets across multiple product lines can be effectively modeled. This research provides valuable insights into optimizing maintenance policies and enhancing the reliability and safety of aircraft engines.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhou, Dr Hang
• Authors: Zhou, H., Parlikad, A. K., Brintrup, A., and Harrison, A.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: Probabilistic Engineering Mechanics
• Publisher: Elsevier
• ISSN: 0266-8920
• ISSN (Online): 1878-4275
• Published Online: 21 June 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Probabilistic Engineering Mechanics 73: 103481
• Publisher Policy: Reproduced under a Creative Commons licence