Probabilistic Assessment of Failure for United States Air Force Building Systems
Publication: Journal of Performance of Constructed Facilities
Volume 31, Issue 5
Abstract
Deteriorating and failing federal facilities represent a significant cost to the U.S. government. In maintaining these assets, the United States Air Force currently uses a facility data system to assess the reliability of building components; however, the necessary probabilities of failure are not predicted. This paper proposes a probabilistic model by using fault trees with fuzzy logic to predict the probability of failure, and therefore reliability, at the system level of a building’s infrastructure hierarchy. Through the ordered weighted averaging (OWA) operator, the method provides a basis for risk assessment by weighting probabilities of failure with the consequences of failure. After validating the method using real-world Air Force data, the proposed OWA model is statistically shown to be a significant improvement over the current condition index method for predicting future repair and replacement needs for building systems. The additional insight provided by the probability-based model provides another tool to evaluate building systems. This should help facility engineers and managers develop more effective long-term strategies to maintain systems and defend their budgetary requirements.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors appreciate the support received from the Air Force Civil Engineer Center and the U.S. Army Engineer Research and Development Center Construction Engineering Research Laboratory. This research would not have been possible without the professionalism and expertise of the individuals at these two organizations.
References
AS/NZS (Australian New Zealand Standard). (2004). “Risk management.” AS/NZS 4360, Standards Australia, Sydney, Australia.
BUILDER version 3.0 [Computer software]. U.S. Army Corps of Engineers, ERDC-CERL, Champaign, IL.
Charette, R. P., and Marshall, H. E. (1999). UNIFORMAT II elemental classification for building specifications, cost estimating, and cost analysis, U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, Gaithersburg, MD.
DUSD(I&E) (Deputy Under Secretary of Defense Installations and Environment). (2015). “FY 2015 base structure Rep.” Dept. of Defense, Washington, DC.
Fullwood, R. R. (2000). Probabilistic safety assessment in the chemical and nuclear industries, Butterworth-Heinemann, Boston.
Grussing, M. N. (2012). Facility degradation and prediction models for sustainment, restoration, and modernization (SRM) planning, U.S. Army Corps of Engineers Engineer Research and Development Center Construction Engineering Research Laboratory (USACE ERDC-CERL), Champaign, IL.
Grussing, M. N., and Liu, L. Y. (2014). “Knowledge-based optimization of building maintenance, repair, and renovation activities to improve facility life cycle investments.” J. Perform. Constr. Facil., 539–548.
Grussing, M. N., and Marrano, L. R. (2007). “Building component lifecycle repair/replacement model for institutional facility management.” Proc., Int. Workshop on Computing in Civil Engineering, ASCE, Reston, VA, 550–557.
Grussing, M. N., Uzarski, D. R., and Marrano, L. R. (2006). “Condition and reliability prediction models using the Weibull probability distribution.” Proc., 9th Int. Conf. Applications of Advanced Technologies in Transportation, ACSE, Reston, VA, 19–24.
Labi, S. (2014). Introduction to civil engineering systems, John Wiley & Sons, Hoboken, NJ.
Muller, B. (1999). Air force instruction 32-1001 operations management, Dept. of the Air Force, Washington, DC.
Oracle version 11g [Computer software]. Oracle Corporation, Redwood Shores, CA.
Ottoman, G. R., Nixon, W. B., and Lofgren, S. T. (1999). “Budgeting for facility maintenance and repair. I: Methods and models.” J. Manage. Eng., 71–83.
Ross, T. J., and Donald, S. (1996). “A fuzzy logic paradigm for fault trees and event trees in risk assessment.” Computing in civil engineering, ASCE, New York, 369–375.
Schlotzhauer, S. D. (2007). Elementary statistics using JMP, SAS Institute, Cary, NC.
Straker, D. (1995). A toolbook for quality improvement and problem solving, Prentice Hall, Englewood Cliffs, NJ.
USACE ERDC-CERL (U.S. Army Corps of Engineers Engineer Research and Development Center-Construction Engineering Research Laboratory). (2007). BUILDER EMS Version 3 user manual, Champaign, IL.
USACE (U.S. Army Corps of Engineers). (2014a). “BUILDER-SMS training materials: BUILDER fundamentals.” ⟨http://sms.cecer.army.mil/SitePages/BUILDER%20Training.aspx⟩ (Apr. 14, 2014).
USACE (U.S. Army Corps of Engineers). (2014b). “BUILDER-SMS training materials: BUILDER indices.” ⟨http://sms.cecer.army.mil/SitePages/BUILDER%20Training.aspx⟩ (Apr. 14, 2014).
USACE (U.S. Army Corps of Engineers). (2014c). “BUILDER-SMS training materials: BUILDER reference books.” ⟨http://sms.cecer.army.mil/SitePages/BUILDER%20Training.aspx⟩ (Apr. 14, 2014).
Uzarski, D. R., and Grussing, M. N. (2006). Condition assessment manual for building component-sections, U.S. Army Engineer Research and Development Center Construction Engineering Research Laboratory, Champaign, IL.
Vesely, W. E., Goldberg, F. F., Roberts, N. H., and Haasl, D. F. (1981). Fault tree handbook, U.S. Nuclear Regulatory Commission, Washington, DC.
Yager, R. R. (1988). “On ordered weighted averaging aggregation operators in multicriteria decisionmaking.” IEEE Trans. Sys. Man Cybern., 18(1), 183–190.
Information & Authors
Information
Published In
Journal of Performance of Constructed Facilities
Volume 31 • Issue 5 • October 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Aug 27, 2016
Accepted: Mar 28, 2017
Published online: Jun 28, 2017
Published in print: Oct 1, 2017
Discussion open until: Nov 28, 2017
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.