Safety and reliability in aviation – A systematic scoping review of normal accident theory, high-reliability theory, and resilience engineering in aviation

Muecklich, Nadine; Sikora, Ivan; Paraskevas, Alexandros; Padhra, Anil

doi:10.1016/j.ssci.2023.106097

Cited by 22 publications

(3 citation statements)

References 78 publications

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“…For the analysis of the risk during the approach and landing phase in aeronautical accidents, and by the literature review, the variables that have a determining impact on the safety of this part of the flight were identified: runway, crew, type of approach, external conditions of the aerodrome and type of aircraft (Bernsmed, et al, 2022). For Configuring the AHP proposed model, the variables mentioned above were analysed by four (4) pilot experts in the aeronautical sector (instructor pilots), based on risk management criteria in a stabilised approach scenario, to finally establish a series of alternatives to achieve a safe air operation (Muecklich, et al, 2023).…”

Section: Methodsmentioning

confidence: 99%

Analytical Hierarchy Process for Risk Management in the Stabilized Flight Approach - Expert Judgment

Pedroza,

Peña,

Sepúlveda-Cano

et al. 2024

DUTCH J FINANCE MANA

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Destabilised approaches have been the primary cause of fatal accidents during the approach and landing phase, as stated in  (Airbus, 2023). The stabilised approach concept is of great importance for the safe operation of an airline during the approach and landing phases (Acarbay & Kiyak, 2020). The elements highlighted in the approach phases are the runway's dry or contaminated condition and length. In the crew, we analyse their competence, recurrence, and fatigue. Another variable is the type of approach, whether it is precision, non-precision or visual. The external conditions of the aerodrome include obstacles, wind, and wildlife—the type of aircraft, whether light, medium or heavy.  Due to the large amount of qualitative information derived from the pilots' experience about risk management in the approach and landing phases, this paper proposes an Analytic Hierarchy Process model (AHP) for threat characterisation and risk analysis to achieve a stabilised approach. The results show that AHP proposed model establishes a new methodology for identifying potential in-flight risks to air operations based on expert criteria, improving the decisions to land at an alternate airport based on qualitative information from expert pilots in the risk management field.

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Section: Methodsmentioning

confidence: 99%

Analytical Hierarchy Process for Risk Management in the Stabilized Flight Approach - Expert Judgment

Pedroza,

Peña,

Sepúlveda-Cano

et al. 2024

DUTCH J FINANCE MANA

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“…Therefore, four abilities characterize resilient organizations and are applicable to SMS: (1) the ability to respond to current challenges; (2) the ability to monitor incoming critical situations; (3) the ability to anticipate the occurrence of future events; and (4) the ability to learn from the past [40]. Further, a systematic review evaluated resilience engineering among other theoretical perspectives in the aviation safety context [41]. Although resilience engineering was the dominant approach, the analysis shows that past studies mainly looked at the primary operational aviation subsystems (air traffic control and flight operations).…”

Section: Safety Management In Aviationmentioning

confidence: 99%

Exploring Safety Culture in Urban Air Mobility: System of Systems Perspectives Using Enterprise Architecture

Hoffmann,

Nishimura,

Gomes

2024

Systems

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Urban Air Mobility (UAM) is an emerging industry marked by technological advancements, new operational contexts, and regulatory frameworks. This article examines how to improve safety management in UAM operations by adopting a just culture approach from a system of systems perspective. Acknowledging the critical role of front-line workers, especially in the early stage with piloted vehicles, the ecosystem-level approach comprehends multiple providers, operators, and services. Employing an enterprise architecture methodology, we address the challenge of fostering a learning-oriented environment amidst diverse organizational perspectives and stakeholders’ interests. This study identifies key capabilities, functions, and resource exchanges within and across organizations by strategically leveraging architectural views and systemic visualizations. A unified safety committee is discussed and recommended to facilitate consensus among stakeholders, including regulatory bodies, thus paving the way for industry-wide improvements. Findings contribute to evolving safety protocols in UAM operations and serve as a blueprint for integrating cutting-edge methodologies to drive systemic enhancements.

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“…Aeroengine risk assessment methods fall into two main categories: model-based and data-driven [5]. Model-based methods mainly rely on mathematical models of the system, but they are sensitive to disturbances, and they cannot solve uncertainties that may arise during operation [6]. Moreover, the high complexity of an aeroengine system often presents challenges to establishing a model.…”

Section: Introductionmentioning

confidence: 99%

Multi-Head Attention-Based Hybrid Deep Neural Network for Aeroengine Risk Assessment

Li,

Gao,

et al. 2023

IEEE Access

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Existing deep-learning models have limited applicability to aeroengine risk assessment owing to insufficient feature extraction capabilities and low robustness. This paper presents a hybrid deep neural network based on a Time2Vec time-embedding layer and multi-head attention mechanism for the proactive risk assessment of aeroengines. The proposed model uses quick access recorder data as input to identify risks associated with different types of failures and outputs two sets of labels: risk level and risk cause. The base of the proposed model combines a convolutional neural network and bidirectional long short-term memory, which are used to automatically extract temporal and spatial features from the input data to represent the system state and capturing irregular temporal trends. The Time2Vec layer facilitates automated processing of sequential data to make it easier for these deep-learning models to recognize patterns in the dataset. The multi-head attention mechanism further enhances the ability of the proposed model to capture and allocate information weights effectively. In comparative experiments, five benchmark models were compared with the proposed model, which demonstrated the best classification accuracy and computational efficiency as well as the most robustness against imbalanced data samples.INDEX TERMS aeroengine risk assessment, hybrid deep neural network, multi-head attention mechanism, Time2Vec

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Safety and reliability in aviation – A systematic scoping review of normal accident theory, high-reliability theory, and resilience engineering in aviation

Cited by 22 publications

References 78 publications

Analytical Hierarchy Process for Risk Management in the Stabilized Flight Approach - Expert Judgment

Analytical Hierarchy Process for Risk Management in the Stabilized Flight Approach - Expert Judgment

Exploring Safety Culture in Urban Air Mobility: System of Systems Perspectives Using Enterprise Architecture

Multi-Head Attention-Based Hybrid Deep Neural Network for Aeroengine Risk Assessment

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