A Web-Based Decision Support System for Aircraft Dispatch and Maintenance

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.

[1]  Premaratne Samaranayake,et al.  Aircraft maintenance planning and scheduling : an integrated framework , 2012 .

[2]  Partho P Sengupta,et al.  Mobile technology and the digitization of healthcare. , 2016, European Heart Journal.

[3]  Qian Song,et al.  Decision support system (DSS) use and decision performance: DSS motivation and its antecedents , 2017, Inf. Manag..

[4]  Karla Hoffman,et al.  Estimating domestic US airline cost of delay based on European model , 2013 .

[5]  Baoguang Xu,et al.  Integrated recovery of aircraft and passengers after airline operation disruption based on a GRASP algorithm , 2016 .

[6]  Rui Li,et al.  Toward a methodology of requirements definition for prognostics and health management system to support aircraft predictive maintenance , 2020 .

[7]  Rui Melício,et al.  Stress, Pressure and Fatigue on Aircraft Maintenance Personal , 2019, International Review of Aerospace Engineering (IREASE).

[8]  Albert Steiner A heuristic method for aircraft maintenance scheduling under various constraints , 2006 .

[9]  Amedeo R. Odoni,et al.  Modelling delay propagation within an airport network , 2013 .

[10]  Richard Curran,et al.  A practical dynamic programming based methodology for aircraft maintenance check scheduling optimization , 2020, Eur. J. Oper. Res..

[11]  George Chryssolouris,et al.  An approach to operational aircraft maintenance planning , 2010, Decis. Support Syst..

[12]  Diego Galar,et al.  Effects of condition-based maintenance on costs caused by unscheduled maintenance of aircraft , 2016 .

[13]  Richard Curran,et al.  Multi-criteria weighted decision making for operational maintenance processes , 2017 .

[14]  Graham Pervan,et al.  A critical analysis of decision support systems research , 2005, J. Inf. Technol..

[15]  K. Eisenhardt Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[16]  Daniel J. Power,et al.  Decision systems redux , 2019, J. Decis. Syst..

[17]  Daniel J. Power,et al.  Computerized Decision Support Case Study Research: Concepts and Suggestions , 2016 .

[18]  Yu-Hern Chang,et al.  Significant human risk factors in aircraft maintenance technicians , 2010 .

[19]  Melike Nikbay Optimization of Aircraft Utilization by Reducing Scheduled Maintenance Downtime , 2009 .

[20]  Zhizhong Li,et al.  Effects of Information Acquisition Method on Diagnostic Task Performance Using Digitalized Interfaces , 2017, AHFE.

[21]  Richard Curran,et al.  Airline delay management problem with airport capacity constraints and priority decisions , 2017 .

[22]  Andrew J. Cook,et al.  The cost of delay to air transport in Europe: quantification and management , 2009 .

[23]  Andrew J. Cook,et al.  Dynamic cost indexing – Managing airline delay costs , 2009 .

[24]  Mohammadsadegh Mobin,et al.  Maintenance decision making, supported by computerized maintenance management system , 2016, 2016 Annual Reliability and Maintainability Symposium (RAMS).

[25]  Daniel J. Power,et al.  Decision Support Systems Discipline: Achievements and Needs , 2006, J. Decis. Syst..

[26]  Xue Yang,et al.  Risk information for operational decision-making in the offshore oil and gas industry , 2016 .

[27]  T. Paul Robert,et al.  Human factors engineering in aircraft maintenance: a review , 2015 .

[28]  Stephen Anderson,et al.  Evaluating the true cost to airlines of one minute of airborne or ground delay: final report , 2004 .

[29]  Graham Pervan,et al.  Eight key issues for the decision support systems discipline , 2008, Decis. Support Syst..

[30]  Wim J. C. Verhagen,et al.  Predictive maintenance for aircraft components using proportional hazard models , 2018, J. Ind. Inf. Integr..