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An expert system framework to support aircraft accident and incident investigations

Published online by Cambridge University Press:  16 March 2021

C.B.R. Ng Open the ORCID record for C.B.R. Ng [Opens in a new window] ,
C. Bil  and
T. O’Bree
C.B.R. Ng*
Affiliation:
School of Engineering RMIT University, Building 251 264 Plenty Road, Mill Park, Bundoora, VIC3083, Australia
C. Bil
Affiliation:
School of Engineering RMIT University, Building 251 264 Plenty Road, Mill Park, Bundoora, VIC3083, Australia
T. O’Bree
Affiliation:
Australian Transport Safety Bureau, Level 1 62 Northbourne Avenue, Canberra, ACT2601, Australia
*
[email protected]
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Abstract

The International Civil Aviation Organisation (ICAO) audits its Member States for safety oversight and monitors its Effective Implementation (EI). The global average EI was 68.83% in 2019, with 46% audited Member States achieving 75% EI (2022 target); however, an ICAO (2016 – 2018) audit highlighted six Annex 13 non-compliance issues. One issue was that more than 60% of Member States do not have a comprehensive and detailed investigator training program, contributing to many shortcomings that include a lack of essential and volatile evidence preservation, investigation management, investigation reporting and/or safety recommendations. This paper proposes an Expert System that captures knowledge in aircraft accident investigation generated over many years and allows aircraft investigators to share, access and interrogate accumulated knowledge to support the aircraft accident investigation process. The Expert System will improve the evidence analysing timeline, conclusion consistency and accuracy and support the on-the-job “field” training of evidence analysis through self-discovery.

Keywords

ICAO Annex 13reason modelaircraft accident and incident investigationsExpert System
Type
Research Article
Information
The Aeronautical Journal , Volume 125 , Issue 1289 , July 2021 , pp. 1131 - 1156
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Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

REFERENCES

International Civil Aviation Organization (ICAO), Manual of Aircraft Accident and Incident Investigation (Doc 9756), Part three, 1st edition, 2011, in Investigation, International Civil Aviation Organization (ICAO), Editor. 2011, ICAO, 999 University Street, Montréal, Quebec, Canada H3C 5H7: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organization (ICAO), Aircraft accident and incident investigation, ICAO Annex 13, 12th edition, July 2020, International Civil Aviation Organization (ICAO), Editor. 2020, International Civil Aviation Organization: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organization. About ICAO. [cited 2020 14 Jan 2020]; Available from: https://www.icao.int/about-icao/Pages/default.aspxGoogle Scholar
International Civil Aviation Organization (ICAO), Convention on international civil aviation done at Chicago on the 7th day of December 1944, International Civil Aviation Organisation (ICAO), Editor. 1944, International Civil Aviation Organization: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organization (ICAO), ICAO Safety Report 2020 Edition, State of Global Aviation Safety. 2020, International Civil Aviation Organization: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organisation (ICAO), Universal Safety Oversight Audit Programme Continuous Monitoring Approach Results - 1 Jan 2016 to 31 Dec 2018. 2019, ICAO: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organization (ICAO), Manual of Aircraft Accident and Incident Investigation (Doc 9756), four parts, in 1. Organisation and Planning, 2. Procedures and Checklists, 3. Investigation, 4. Reporting, International Civil Aviation Organization (ICAO), Editor., ICAO, 999 University Street, Montréal, Quebec, Canada H3C 5H7: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organisation (ICAO). Universal Safety Oversight Audit Programme Continuous Monitoring Approach Results - Safety Audit Results. [cited 2020 21 Aug 2020]; Available from: https://www.icao.int/safety/Pages/USOAP-Results.aspxGoogle Scholar
International Civil Aviation Organisation (ICAO), Universal Safety Oversight Audit Programme Continuous Monitoring Manual, international Civil Aviation Organisation (ICAO), Editor. 2011, International Civil Aviation Organisation: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organization (ICAO), Manual of Aircraft Accident and Incident Investigation (Doc 9756), Part one, 2nd edition, 2015, in Investigation, International Civil Aviation Organization (ICAO), Editor. 2015, ICAO, 999 University Street, Montréal, Quebec, Canada H3C 5H7: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organization (ICAO), Training Guidelines for Aircraft Accident Investigators, Cir 298 AN/172. 2003, International Civil Aviation Organization: ICAO Headquarters, Montreal, Canada.Google Scholar
International Civil Aviation Organisation (ICAO), ICAO Safety Management Manual Fourth Edition, 2018, Doc 9859, International Civil Aviation Organisation (ICAO), Editor. 2018, International Civil Aviation Organisation 999 Robert-Bourassa Boulevard, Montréal, Quebec, Canada H3C 5H7.Google Scholar
International Civil Aviation Organisation, Annex 19 to the Convention on International Civil Aviation: Safety Management. 2016, International Civil Aviation Organisation: 999 Robert-Bourassa Boulevard, Montréal, Quebec, Canada H3C 5H7.Google Scholar
International Civil Aviation Organization (ICAO), ICAO Member States official list – 193 in total. 2019, International Civil Aviation Organization: ICAO Headquarters, Montreal, Canada.Google Scholar
Australian Transport Safety Bureau (ATSB). ATSB Main Web Page. [cited 2020 23 Sep 2020]; Available from: https://www.atsb.gov.au/Google Scholar
Walker, M.B. and Bills, K.M., ATSB TRANSPORT SAFETY REPORT Aviation Research and Analysis Report AR-2007-053, in Analysis, Causality and Proof in Safety Investigations. 2008, Australian Transport Safety Bureau: Australia.Google Scholar
Turban, E. and Aronson, J.E. Decision support systems and intelligent systems. 6th ed. ed, ed. Aronson, J.E.. Prentice Hall, 2001, Upper Saddle River, NJ.Google Scholar
Tan, H. A brief history and technical review of the expert system research. 2017.10.1088/1757-899X/242/1/012111CrossRefGoogle Scholar
Tan, C., et al., The application of expert system: A review of research and applications. J Engineering and Applied Sciences, 2016, 11 (4).Google Scholar
Sheikhtaheri, A., Sadoughi, F. and Hashemi Dehaghi, Z. Developing and Using Expert Systems and Neural Networks in Medicine: A Review on Benefits and Challenges. J Medical Systems, 2014, 38 (9), pp 1–6.10.1007/s10916-014-0110-5CrossRefGoogle Scholar
Liao, S.-H. Problem structuring methods in military command and control. Expert Systems With Applications, 2008, 35 (3), pp 645–653.10.1016/j.eswa.2007.07.012CrossRefGoogle Scholar
Ameneh, K. and Fatemeh Mohammadi, A. A fuzzy expert system for diagnosis and treatment of musculoskeletal disorders in wrist. Tehnički Vjesnik, 2017, 24 (Supplement 1), pp 147–155.Google Scholar
Jabbar, H.K. and Khan, R.Z. Tools of development of expert systems: A comparative study. in 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom). 2016.Google Scholar
Abu-Nasser, B.S. Medical Expert Systems Survey. Int J Engineering and Information Systems, 2017, 1 (7), pp 218–224.Google Scholar
Nagori, V. and Trivedi, B. Types of Expert System: Comparative Study. Asian J Computer and Information Systems, 2014, 02 (02).Google Scholar
Qiu, J., et al., A survey of machine learning for big data processing. EURASIP J Advances in Signal Processing, 2016, 2016 (1), pp 1–16.Google Scholar
MathWorks. MathWorks Main Web Page - Matlab, Simulink. [cited 2020 25 Sep 2020]; Available from: https://au.mathworks.com/Google Scholar
Rebala, G.a., Ravi, A. and Churiwala, S. An Introduction to Machine Learning, ed. A.a. Ravi, S.a. Churiwala, and SpringerLink. 2019, Cham: Springer International Publishing: Imprint: Springer.10.1007/978-3-030-15729-6CrossRefGoogle Scholar
Chug, A. and Dhall, S. Software Defect Prediction Using Supervised Learning Algorithm and Unsupervised Learning Algorithm. IET, 2013, Stevenage, UK. p. 5.01.10.1049/cp.2013.2313CrossRefGoogle Scholar
Mathworks. Foundation of Fuzzy Logic. [cited 2020 25 Feb 2020]; Available from: https://au.mathworks.com/help/fuzzy/foundations-of-fuzzy-logic.html?s_tid=srchtitleGoogle Scholar
Sremac, S., et al., Neuro-fuzzy inference systems approach to decision support system for economic order quantity. Economic Research-Ekonomska Istraživanja, 2019, 32 (1), pp 1114–1137.10.1080/1331677X.2019.1613249CrossRefGoogle Scholar
Bobek, S. and Misiak, P. Framework for benchmarking rule-based inference engines. 2017. pp 399–410.10.1007/978-3-319-59060-8_36CrossRefGoogle Scholar
Kour, H., Manhas, J. and Sharma, V. Evaluation of Adaptive Neuro-Fuzzy Inference System with Artificial Neural Network and Fuzzy Logic in Diagnosis of Alzheimer Disease. in 2019 6th International Conference on Computing for Sustainable Global Development (INDIACom). 2019.10.33851/JMIS.2019.6.2.87CrossRefGoogle Scholar
Nitin, K., Sunita, and Smita, Comparison of ANNs, Fuzzy Logic and Neuro-Fuzzy Integrated Approach for Diagnosis of Coronary Heart Disease - A Survey. Int J Computer Science and Mobile Computing, 2013, 2 (6), pp 216–224.Google Scholar
Abraham, A. Adaptation of Fuzzy Inference System Using Neural Learning. Vol. 181. Springer Berlin Heidelberg, 2005, Berlin, Heidelberg, pp 53–83.Google Scholar
Henderson, C. Bayesian networks: A guide for their application in natural resource management and policy March. 2010.Google Scholar