Measuring and Optimizing for Infrastructure Endurance
Publication: Journal of Performance of Constructed Facilities
Volume 38, Issue 4
Abstract
Optimal facility repair planning is a challenge, especially as it applies to a portfolio of facilities constrained by a limited budget. This paper discusses a linear programming optimization method to develop improved maintenance and repair strategies. This method introduces a utility metric, termed component “endurance,” used to determine repair decisions to help maximize the financial health of a portfolio of facilities. A predictive model is used to calculate this endurance metric to measure the impact of repair decisions at a specified future date. This future impact is integrated into an optimization framework to guide repair decisions with the aim of avoiding excessive deterioration of the most valuable components while remaining within budget. This approach shows appreciable benefits over traditional component condition ranking approaches, including increased portfolio health and reductions in deferred maintenance.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
References
Alley, S. L., V. V. Valencia, A. E. Thal Jr., and E. D. White III. 2017. “Probabilistic assessment of failure for United States air force building systems.” J. Perform. Constr. Facil. 31 (5): 04017088. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001077.
Bartels, L. B., L. Y. Liu, K. El-Rayes, N. El-Gohary, M. Golparvar, and M. N. Grussing. 2020. “Work optimization with association rule mining of accelerated deterioration in building components.” J. Perform. Constr. Facil. 34 (3): 04020033. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001441.
Betz, T., K. El-Rayes, M. Grussing, K. Landers, and L. Bartels. 2023. “Parametric estimation of equipment failure risk with machine learning and constrained optimization.” J. Perform. Constr. Facil. 37 (1): 04022073. https://doi.org/10.1061/JPCFEV.CFENG-4284.
Carnahan, J. V. 1988. “Analytical framework for optimizing pavement maintenance.” J. Transp. Eng. 114 (3): 307–322. https://doi.org/10.1061/(ASCE)0733-947X(1988)114:3(307).
Clayton, M. J., R. E. Johnson, and Y. Song. 1999. “Operations documents: Addressing the information needs of facility managers.” Durability Build. Mater. Compon. 8 (4): 2441–2451.
Congressional Research Service. 2022. Defense primer: Future years defense program (FYDP). Washington, DC: Congressional Research Service.
Dhulipala, S. L., and M. M. Flint. 2020. “Series of semi-Markov processes to model infrastructure resilience under multihazards.” Reliab. Eng. Syst. Saf. 193 (Feb): 106659. https://doi.org/10.1016/j.ress.2019.106659.
Durango-Cohen, P. L. 2004. “Maintenance and repair decision making for infrastructure facilities without a deterioration model.” J. Infrastruct. Syst. 10 (1): 1–8. https://doi.org/10.1061/(ASCE)1076-0342(2004)10:1(1).
Durango-Cohen, P. L., and S. M. Madanat. 2008. “Optimization of inspection and maintenance decisions for infrastructure facilities under performance model uncertainty: A quasi-Bayes approach.” Transp. Res. Part A Policy Pract. 42 (8): 1074–1085. https://doi.org/10.1016/j.tra.2008.03.004.
Ebeling, C. E. 2019. An introduction to reliability and maintainability engineering. Long Grove, IL: Waveland Press.
Elbehairy, H., E. Elbeltagi, T. Hegazy, and K. Soudki. 2006. “Comparison of two evolutionary algorithms for optimization of bridge deck repairs.” Comput.-Aided Civ. Infrastruct. Eng. 21 (8): 561–572. https://doi.org/10.1111/j.1467-8667.2006.00458.x.
Estes, A. C., and D. M. Frangopol. 1999. “Repair optimization of highway bridges using system reliability approach.” J. Struct. Eng. 125 (7): 766. https://doi.org/10.1061/(ASCE)0733-9445(1999)125:7(766).
Faddoul, R., W. Raphael, and A. Chateauneuf. 2018. “Maintenance optimization of series systems subject to reliability constraints.” Reliab. Eng. Syst. Saf. 180 (Jun): 179–188. https://doi.org/10.1016/j.ress.2018.07.016.
GAO (United States Government Accountability Office). 2022. Defense infrastructure DOD should manage risked posed by deferred facility maintenance. GAO-22-104481. Washington, DC: GAO.
Gonzalez-Dominguez, J., G. Sanchez-Barroso, and J. Garcia-Sanz-Calcedo. 2020. “Preventive maintenance optimisation of accessible flat roofs in healthcare centres using the Markov chain.” J. Build. Eng. 32 (Nov): 101775. https://doi.org/10.1016/j.jobe.2020.101775.
Grussing, M., S. Gunderson, M. Canfield, E. Falconer, A. Antelman, and S. Hunter. 2010. Development of the army facility mission dependency index for infrastructure asset management. Washington, DC: Engineer Research and Development Center.
Grussing, M. N., L. Y. Liu, D. R. Uzarski, K. El-Rayes, and N. El-Gohary. 2016. “Discrete Markov approach for building component condition, reliability, and service-life prediction modeling.” J. Perform. Constr. Facil. 30 (5): 04016015. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000865.
Grussing, M. N., and L. R. Marrano. 2007. “Building component lifecycle repair/replacement model for institutional facility management.” In Computing in civil engineering (2007), 550–557. Reston, VA: ASCE.
Idoniboyeobu, D. C., B. C. Wokoma, and V. C. Ibanibo. 2018. “Preventive maintenance for substation with aging equipment using Weibull distribution.” Am. J. Eng. Res. 7 (Jan): 95–101.
Jaafaru, H., and B. Agbelie. 2022. “Bridge maintenance planning framework using machine learning, multi-attribute utility theory and evolutionary optimization models.” Autom. Constr. 141 (Jun): 104460. https://doi.org/10.1016/j.autcon.2022.104460.
Jin, Y., and A. Mukherjee. 2014. “Markov chain applications in modelling facility condition deterioration.” Int. J. Crit. Infrastruct. 10 (2): 93–112. https://doi.org/10.1504/IJCIS.2014.062965.
Kobayashi, K., K. Kaito, and N. Lethanh. 2012. “A statistical deterioration forecasting method using hidden Markov model for infrastructure management.” Transp. Res. Part B Methodol. 46 (4): 544–561. https://doi.org/10.1016/j.trb.2011.11.008.
Kuhn, K. D., and S. M. Madanat. 2005. “Model uncertainty and the management of a system of infrastructure facilities.” Transp. Res. Part C Emerging Technol. 13 (5–6): 391–404. https://doi.org/10.1016/j.trc.2006.02.001.
Kulkarni, R. B. 1984. “Dynamic decision model for a pavement management system.” Transp. Res. Rec. 997 (1): 11–18.
Lee, K., and Y. Jung. 2016. “Assessment of facility management functions for life-cycle information sharing.” Korean J. Constr. Eng. Manage. 17 (6): 40–52. https://doi.org/10.6106/KJCEM.2016.17.6.040.
Li, N., W. C. Xie, and R. Haas. 1996. “Reliability-based processing of Markov chains for modeling pavement network deterioration.” Transp. Res. Rec. 1524 (1): 203–213. https://doi.org/10.1177/0361198196152400124.
Macchi, M., M. Garetti, D. Centrone, L. Fumagalli, and G. P. Pavirani. 2012. “Maintenance management of railway infrastructures based on reliability analysis.” Reliab. Eng. Syst. Saf. 104 (Feb): 71–83. https://doi.org/10.1016/j.ress.2012.03.017.
Marseguerra, M., and E. Zio. 2000. “Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation.” Reliab. Eng. Syst. Saf. 68 (1): 69–83. https://doi.org/10.1016/S0951-8320(00)00007-7.
Nozhati, S., Y. Sarkale, B. Ellingwood, E. K. Chong, and H. Mahmoud. 2019. “Near-optimal planning using approximate dynamic programming to enhance post-hazard community resilience management.” Reliab. Eng. Syst. Saf. 181 (Mar): 116–126. https://doi.org/10.1016/j.ress.2018.09.011.
Onyango, M., S. A. Merabti, J. Owino, I. Fomunung, and W. Wu. 2018. “Analysis of cost effective pavement treatment and budget optimization for arterial roads in the city of Chattanooga.” Front. Struct. Civ. Eng. 12 (3): 291–299. https://doi.org/10.1007/s11709-017-0419-5.
Orcesi, A. D., and C. F. Cremona. 2010. “A bridge network maintenance framework for Pareto optimization of stakeholders/users costs.” Reliab. Eng. Syst. Saf. 95 (11): 1230–1243. https://doi.org/10.1016/j.ress.2010.06.013.
Park, K., N. E. Thomas, and K. W. Lee. 2007. “Applicability of the international roughness index as a predictor of asphalt pavement condition1.” J. Transp. Eng. ASCE 133 (12): 706–709. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:12(706).
Peralta, D., C. Bergmeir, M. Krone, M. Galende, M. Menéndez, G. I. Sainz-Palmero, C. Martinez Bertrand, F. Klawonn, and J. M. Benitez. 2018. “Multiobjective optimization for railway maintenance plans.” J. Comput. Civ. Eng. 32 (3). https://doi.org/10.1061/(ASCE)CP.1943-5487.0000757.
Pint, E. M., B. E. Lachman, K. Anania, and C. P. Jackson. 2020. Improving the allocation and execution of army facility sustainment funding. Santa Monica, CA: RAND.
Robelin, C. A., and S. M. Madanat. 2008. “Reliability-based system-level optimization of bridge maintenance and replacement decisions.” Transp. Sci. 42 (4): 508–513. https://doi.org/10.1287/trsc.1080.0241.
Rockette, H., C. Antle, and L. A. Klimko. 1974. “Maximum likelihood estimation with the Weibull model.” J. Am. Stat. Assoc. 69 (345): 246–249.
Sattar, A. M., Ö. F. Ertuğrul, B. Gharabaghi, E. A. McBean, and J. Cao. 2019. “Extreme learning machine model for water network management.” Neural Comput. Appl. 31 (1): 157–169. https://doi.org/10.1007/s00521-017-2987-7.
SMS (Sustainment Management System). 2020. “Sustainment management system.” Accessed September 22, 2020. https://www.sms.erdc.dren.mil/#portfolioModal7.
Tack, J. N., and J. Chou. 2002. “Multiyear pavement repair scheduling optimization by preconstrained genetic algorithm.” Transp. Res. Rec. 1816 (1): 3–8. https://doi.org/10.3141/1816-01.
Thomas, O., and J. Sobanjo. 2013. “Comparison of Markov chain and semi-Markov models for crack deterioration on flexible pavements.” J. Infrastruct. Syst. 19 (2): 186–195. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000112.
Tian, Q., and H. Wang. 2022. “Optimization of preventive maintenance schedule of subway train components based on a game model from the perspective of failure risk.” Sustainable Cities Soc. 81 (Apr): 103819. https://doi.org/10.1016/j.scs.2022.103819.
Uzarski, D. R., and L. A. Burley. 1997. “Assessing building condition by the use of condition indexes.” In Infrastructure condition assessment: Art, science, and practice, 365–374. Reston, VA: ASCE.
Wang, K. C. P., J. Zaniewski, and G. Way. 1994. “Probabilistic behavior of pavements.” J. Transp. Eng. 120 (3): 358–375. https://doi.org/10.1061/(ASCE)0733-947X(1994)120:3(358).
Wenfei, B., W. Yun, and L. Rengkui. 2022. “Optimization model of life cycle repair decisions for track network.” J. Transp. Eng. Part A. Syst. 148 (6): 04022032. https://doi.org/10.1061/JTEPBS.0000667.
Information & Authors
Information
Published In
Journal of Performance of Constructed Facilities
Volume 38 • Issue 4 • August 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Dec 7, 2023
Accepted: Mar 14, 2024
Published online: Jun 11, 2024
Published in print: Aug 1, 2024
Discussion open until: Nov 11, 2024
ASCE Technical Topics:
- Architectural engineering
- Budgets
- Building management
- Business management
- Computer programming
- Computing in civil engineering
- Construction engineering
- Construction methods
- Engineering fundamentals
- Financial management
- Infrastructure
- Linear functions
- Maintenance and operation
- Mathematical functions
- Mathematics
- Measurement (by type)
- Metric systems
- Practice and Profession
- Rehabilitation
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.