UNCERTAINTY ASSESSMENT OF AIRCRAFT MAINTENANCE TIMES
This thesis demonstrates the use of the Dempster-Shafer Theory of evidence as a decision aid to specify
maintenance time during wartime operations, by the help of expert judgment elicitation. This more precise time
estimation enables the decision maker to make more accurate decisions for Air Force’s wartime tactical
operations allowing commanders to gain a decisive advantage. The major failures were modeled as assessments
to investigate maintenance times. A questionnaire was tailored to elicit judgment from experts at the Aircraft
Maintenance Facility (AMF). Through an application of the Dempster-Shafer Theory, expert judgment
elicitation was determined to be the critical data. This approach was presented as a plausible evidence
combination technique when uncertain, incomplete, and incorrect evidence must be assessed during wartime
environment. Jet engine aircraft failures examples that met two classes of uncertainty, aleatory and epistemic,
were presented to demonstrate possible maintenance time during wartime operations. A decision aid based on
the Dempster-Shafer Theory was created and an uncertainty assessment is discussed. This decision aid allows a
comparison of each expert’s assessment. The results of this methodology provide a useful and specific
application area for the Dempster-Shafer Theory and the AMF in aiding a decision maker to assess the level of
an expert’s uncertainty.
1989). On the Uses of Expert Judgment on Complex
Technical Problems. Transactions On Engineering
Management (Vol. 36, No. 2), 83-86.
 Booker, J. M., & L.A. Mc Namara(2004).
Expert Knowledge in Realibilty Characterization: A
Rigorous Approach to Eliciting, Documenting, and
Analyzing Expert Knowledge. Los Alamos NAtional
Laboratory: CRC Press LLC.
 Hora, S., & Jensen, M. (2002). Expert
Judgement Elicitation. Swedish Radiation Protection
 Haimes, Y. Y. (1998). Risk Modeling,
Assessment and Management. John Wiley & Sons:
 Booker, J. M., & Meyer, M. A. (2004).
Uncertainty Quantification: Methods and Examples
from Probability and Fuzzy Theories. Los Alamos
 Helton, J., Johnson, J., Oberkampf, W., &
Storlie, C. (2007). A Sampling-based Computational
Strategy for the Representation of Epistemic
Uncertainty in Model Predictions with Evidence
Theeory. Computational Methods Application
Mechanical Engineering (196), 3980-3998.
 Oberkampf, W. L. (2005). Uncertainty
Quantification Using Evidence Theory. Advanced
Simulation & Computing Workshop Error Estimation,
Uncertainty Quantification,And Reliability in
Numerical Simulations. Albuquerque
 Bae, H.-R., Grandhi, R. V., & Canfield, R. A.
(2003). Uncertainty Quantification of Structural
Response Using Evidence Theory. Air Force Office of
Scientific Research , 41 (10), 2062-2068.
 Pinto, A. (2008). ENMA 724: Risk Analysis.
Department of Engineering Management and Systems
Engineering, Old Dominion University, Spring Term
 Bondi, S.B. (2007). Uncertainty Assessment in
High Risk Environments Using Probability, Evidence
Theory and Expert Judgment Elicitation. Ph.D.
Dissertation. Old Dominion University, Norfolk, VA.
 Dempster, A. (1967). Upper and Lower
Probabilities Induced by Multivalued Mapping. The
Annals of Mathematical Statistics , 38 (2), 325-339.
 Shafer, G. (1976). A Mathematical Theory of
Evidence. New Jersey: Princeton University Press
 Yager, R. R. (1987). On the Dempster-Shafer
Framework and New Combination Rules. Information
Sciences , 93-137.
 Ayyub, B. M. (2001). Elicitation of Expert
Opinions for Uncertainty and Risks. Baco Raton FL:
 Zadeh, L. (1984). Review of Shafer's a
Mathematical Theory of Evidence. Artifical
Intelligence Magazine (5), 81-83.
The manuscript with title and authors is being submitted for publication in Journal of Aeronautics and Space Technologies. This article or a major portion of it was not published, not accepted and not submitted for publication elsewhere. If accepted for publication, I hereby grant the unlimited and all copyright privileges to Journal of Aeronautics and Space Technologies.
I declare that I am the responsible writer on behalf of all authors.