Addressing Aircraft Maintenance Delays Using a DMAIC-FMEA Framework: Insights from a Commercial Aviation Case Study

Aircraft maintenance delays (AMD) remain a significant challenge in commercial aviation, adversely affecting operational efficiency, flight punctuality, and passenger satisfaction. Despite advancements in maintenance strategies, recurring disruptions continue to generate financial losses and reputational risks. This study proposes an integrated five-step framework that combines failure mode and effects analysis (FMEA) with the Define–Measure–Analysis–Improve–Control (DMAIC) methodology to systematically address and reduce AMD. The framework involves the definition of problems, the identification of contributing factors and failure modes, the assessment of risk and root cause analysis, the mitigation of risk, and continuous monitoring. The main contribution of this study lies in the integration of FMEA and DMAIC into a unified data-driven system that proactively reduces maintenance delays, offering a novel approach to continuous process improvement in aviation operations. Its practical applicability is demonstrated through a case study of the AFRIQIYAH Airways Airbus A320 fleet, which represents the majority of the airline’s operations. High-risk landing gear failure modes were identified, evaluated and addressed through targeted improvement projects, including predictive maintenance, supplier diversification, inventory optimization, and improved quality assurance for critical spare parts. Implementing these initiatives is expected to reduce the overall Risk Priority Number (RPN) by approximately 59%, highlighting the effectiveness and potential to minimize AMD.

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Publication Details

Journal
Applied Sciences
Published
2025-11-16
DOI
https://doi.org/10.3390/app152212164
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Addressing Aircraft Maintenance Delays Using a DMAIC-FMEA Framework: Insights from a Commercial Aviation Case Study

Faouzi Masmoudi, Wafik Hachicha, Awad M. Aljuaid, Khaled Aljaly
Applied Sciences
Reliability and Maintenance Optimization
article

Addressing Aircraft Maintenance Delays Using a DMAIC-FMEA Framework: Insights from a Commercial Aviation Case Study

Faouzi Masmoudi, Wafik Hachicha, Awad M. Aljuaid, Khaled Aljaly
article en

Abstract

Aircraft maintenance delays (AMD) remain a significant challenge in commercial aviation, adversely affecting operational efficiency, flight punctuality, and passenger satisfaction. Despite advancements in maintenance strategies, recurring disruptions continue to generate financial losses and reputational risks. This study proposes an integrated five-step framework that combines failure mode and effects analysis (FMEA) with the Define–Measure–Analysis–Improve–Control (DMAIC) methodology to systematically address and reduce AMD. The framework involves the definition of problems, the identification of contributing factors and failure modes, the assessment of risk and root cause analysis, the mitigation of risk, and continuous monitoring. The main contribution of this study lies in the integration of FMEA and DMAIC into a unified data-driven system that proactively reduces maintenance delays, offering a novel approach to continuous process improvement in aviation operations. Its practical applicability is demonstrated through a case study of the AFRIQIYAH Airways Airbus A320 fleet, which represents the majority of the airline’s operations. High-risk landing gear failure modes were identified, evaluated and addressed through targeted improvement projects, including predictive maintenance, supplier diversification, inventory optimization, and improved quality assurance for critical spare parts. Implementing these initiatives is expected to reduce the overall Risk Priority Number (RPN) by approximately 59%, highlighting the effectiveness and potential to minimize AMD.

Applied SciencesVol. 15(22)
University of Sfax (TN), Taif University (SA), Higher Institute of Management (RU), University of Gabès (TN)
Taif University
Openalex Percentile: Top 58%
Reliability and Maintenance Optimization
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