Aircraft dispatch involves determining the optimal dispatch option when an aircraft experiences an unexpected failure. Currently, maintenance technicians at the apron have limited access to support information and finding the right information in extensive maintenance manuals is a time-consuming task, often leading to technically induced delays. This paper introduces a novel web-based prototype decision support system to aid technicians during aircraft dispatch decision-making and subsequent maintenance execution. A system architecture for real-time dispatch decision support is established and implemented. The developed system is evaluated through a case study in an operational environment by licensed maintenance technicians. The system fully automates information retrieval from multiple data sources, performs alternative identification and evaluation for a given fault message, and provides the technician with on-site access to relevant information, including the related maintenance tasks. The case study indicates a potential time saving of up to 98% per dispatch decision. Moreover, it enables digitalization of the—currently mostly paper-based—dispatch decision process, thereby reducing logistics and paper waste. The prototype is the first to provide operational decision support in the aircraft maintenance domain and addresses the lack of correlation between theory and practice often found in decision support systems research by providing a representative case study. The developed custom parser for SGML-based documents enables efficient identification and extraction of relevant information, vastly contributing to the overall reduction of the decision time.

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When an aircraft experiences an unexpected issue during flight operations, a technician determines whether the aircraft can safely perform the next flight. This operational decision process - known as dispatch assessment - has to happen within limited available time between aircraft arrival and departure. Currently, technicians face two main problems during the assessment: lack of access to decision support information and a time-consuming process for finding relevant information in extensive maintenance manuals. These issues often lead to delays and additional costs and are indicative of three larger challenges in the decision support domain: 1) a paucity of decision support models and applications for operational processes in maintenance; 2) relatively few efforts in applying and evaluating artifacts in experimental and real-life operational settings; and 3) a lack of systematic development, application and evaluation of digitization and automation efforts of complex decision processes in maintenance. This paper applies a design science research approach to address these challenges and introduces two novel artifacts: a decision support framework for real-time decision making in aircraft dispatch, and a web-based prototype tool accessible through mobile solutions. The practical relevance of the framework and prototype is validated through two representative application and evaluation studies, one in an experimental setting and one in an operational environment. Results show significant time savings and strong qualitative indications towards a higher incentive to use documentation and reducing human risk factors that lead to maintenance error.

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Delays are costly to airlines in both money and image. A significant number of delays is caused by unexpected technical failures of aircraft systems or components. These failures, if not dealt with efficiently, can cause disruptions in the flight schedule and network. The annual costs of these type of disruptions add up to an estimated cost of € 2.8 billion in Europe alone. Determining the optimal course of action when an unexpected failure occurs is currently troublesome, leading to inefficient dispatch decision making.

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The use of documentation for task support in aircraft line maintenance is still mostly paper-based, which is slow, burdensome and prone to error. This paper provides an overview of the issues associated with the use of paper-based documentation in aircraft line maintenance and describes the development of a novel concept for contextualised documentation to address these issues. Using ontology-based data access, the system is able to retrieve relevant documents approximately twice as fast as existing relational database systems and provides support for a wide variety of file types. Limitations of the developed system are software vendor dependency, compatibility issues between integrated software solutions and lack of support for automatic mappings. Nevertheless, the developed system provides a proof of concept for a mobile tool to overcome the weaknesses of maintenance documentation in line maintenance, working towards increased operational efficiency, reduction of human factor induced maintenance errors and reduced paper consumption.@en

The aircraft dispatch decision is a complex analysis based on many factors related to airworthiness regulations, aircraft health status, resource availability at current and future stop(s) and operational preferences of the operator. Within the turnaround time (TAT) a decision has to be made whether the aircraft can return to service, defects have to be deferred, operational restrictions apply, maintenance has to be performed, or if the aircraft is unable to safely perform the next flight. This paper presents a framework for automated dispatch decision support and, as a first step of implementation of the framework, a proof of concept for automated root cause identification by means of a case study on a Airbus A320 wing anti-ice valve. A decision tree algorithm has been applied to a synthetic dataset, representing historical failure data with associated root causes and observed symptoms, achieving correct classification of the root cause for 40% of the cases. Analysis of the results show that the accuracy of the method increases with an increasing number of symptoms associated to a root cause. Furthermore, the method cannot distinguish between root causes with similar symptoms. Although the use of synthetic data restricts conclusions that can be drawn from the results, the work shows a proof of concept for automated root cause identification and leads to initial findings that are essential for future implementation and optimisation of the method. Eventually, the framework will be operationalised in the form of a mobile tool to assist stakeholders in on-site aircraft dispatch decision support.@en

Currently, task support information in aircraft maintenance is mostly provided using paper-based solutions, which are burdensome, slow and prone to error. Aircraft maintenance documentation contains vast amounts of information irrelevant for the task at hand and even for the simplest tasks multiple documents need to be consulted. Next to these issues with the documentation itself, Aircraft Maintenance Technicians (AMTs) have very limited on-site access to support information. These factors lead to 15–20% of hands-on-aircraft time being wasted on acquiring the right information or not using maintenance documentation for task support at all, risking maintenance error. This paper describes the development of a system for a first level of contextualization of maintenance documentation to simplify the retrieval of task support information. Combining a tailor-made ontology with a relational database system for Ontology-Based Data Access (OBDA), maintenance documents relevant to a specific aircraft registration mark can be identified. The system contributes to the research field of knowledge management by using OBDA for selecting relevant maintenance documents stored in a regular file folder. Future work will focus on increasing the level of contextualization, development of a mobile tool for on-site access and prototype verification and validation in an operational environment.@en