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Title: Modelling airport surface safety : a framework for a holistic airport safety management
Author: Wilke, Sabine
ISNI:       0000 0005 0732 5403
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Airports are complex systems involving the continuous interaction of human operators with the physical infrastructure, technology and procedures to ensure the safe and efficient conduct of flights. From an operational perspective, airport surface operations (i.e. runway and taxiway operations) require the interaction of five main stakeholders (i.e. crew or pilots, air traffic control, airport operator, ground handling and regulator) both to facilitate the ground movement of aircraft and vehicles, and to maintain the surface in a working condition. The complexity of these operations makes the runway and taxiway system vulnerable and presents a risk of failure with the consequent potential for the occurrence of accidents. Therefore, the development and implementation of an effective Safety Management System (SMS) are required to ensure the highest level of safety for surface operations. A SMS is a systematic approach to managing safety based on the four cornerstones of safety policy and objectives, risk management, assurance, and safety promotion. Although the International Civil Aviation Organisation (ICAO) provides the global legislative framework for SMS, the relevant regulations are still to be established at the national level with the consequence that practical guidance on the development and implementation of SMS is rare, and reliable tools to support SMS are lacking. The consequence of this is that the current approach to surface safety management is piecemeal and not integrated. Typically, a single accident and incident type is investigated from the perspective of an individual stakeholder with the consequence that resulting proposals for safety mitigation measures are biased and limited in terms of their impact. In addition, the industry is characterised by non-standardised data collection and investigation practices, insufficient or missing definitions, differing reporting levels, and a lack of a coherent and standardised structure for efficient coding and analysis of safety data. Since these shortcomings are a major barrier to the required holistic and integrated approach to safety management, this thesis addresses the four cornerstones of SMS and recommends major enhancements. In particular, a framework for a holistic airport surface safety management is proposed. The framework comprises the static airport architecture, a process model of surface operations, the determination of causal factors underlying failure modes of these operations, a macroscopic scenario tool and a functional relationship model. Safety data and other data sources feed the framework and a dedicated data pre-processing strategy ensures its validity. Unlike current airport surface safety management practices, the proposed framework assesses the safety of the operations of all relevant actors. Firstly, the airport architecture is modelled and the physical and functional variability of airports defined. Secondly, a process model of surface operations is developed, which captures the tasks of the stakeholders and their interactions with physical airport surface infrastructure. This model serves as a baseline model and guides the further development of the airport SMS. To manage the safety of surface operations, the causes of accidents and incidents must be identified and their impacts understood. To do so, a reference data set combining twelve databases from airlines, airport operators, Air Navigation Service Providers (ANSPs), ground handling companies and regulators is collected. Prior to its analysis, the data is assessed for its quality, and in particular, for its internal validity (i.e. precision), external validity (i.e. accuracy) and in terms of reporting levels. A novel external data validation framework is developed and each database is rated with a data quality index (DQI). In addition, recommendations for reporting systems and safety policies are given. Subsequently, the data is analysed for causal factors across stakeholders and the contribution of the individual actors are highlighted. For example, the analysis shows that the various stakeholders capture different occurrence types and underlying causal factors, often including information that is of potential use for another party. The analysis is complemented by interviews, observations and statistical analysis, and the results are summarised in a new taxonomy. This taxonomy is applicable to all relevant stakeholders and is recommended for operational safety risk management. After the airport surface operations have been modelled and the drivers to safety identified, the results are combined, resulting in a macroscopic scenario tool which supports the management of change (i.e. safety assurance), training and education, and safety communication (i.e. safety promotion) functions of the SMS. Finally, a structured framework to assess the functional relationship between airport surface accidents / incidents and their underlying causal factors is proposed and the system is quantified in terms of safety. Compared to the state-of-the-art safety assessments that are biased and limited in terms of their impact, the holistic approach to surface safety allows modelling the safety impact of each system component, their interactions and the entire airport surface system architecture. The framework for a holistic airport surface safety management developed in this thesis delivers a SMS standard for airports. The standard exceeds international requirements by standardizing the two SMS core functions (safety risk management and safety assurance) and integrating safety-relevant information across all relevant stakeholders. This allows a more effective use of safety information and provides an improved overview on, and prediction of, safety risks and ultimately improves the safety level of airports and their stakeholders. Furthermore, the methodology employed in this thesis is flexible and could be applied to all aspects of aviation SMS and system analysis.
Supervisor: Majumdar, Arnab; Ochieng, Washington Sponsor: Lloyd's Register Foundation
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral