Building Optimization Model for Minimizing Operation and Maintenance Costs
Publication: Construction Research Congress 2022
ABSTRACT
Building operation and maintenance costs are reported to be the longest and most costly phase of a building’s lifecycle and it exceeds the total cost of initial design and construction. The present study focuses on developing a new model for optimizing the upgrade and maintenance interventions for existing commercial and residential buildings to minimize their operation and maintenance costs in a predefined period of study while complying with specified annual budgets and building operational performance constraints. The optimization model is developed in three stages: (1) identifying model decision variables, formulating objective function, and constraints; (2) implementing model computations using binary linear programming; and (3) analyzing the performance of the optimization model using a case study. To ensure that the model generates practical solutions, it integrated a set of constraints to comply with annual budgets, components’ service lives, and expected operational performance. The results of the case study analysis showed that the developed model was able to identify the minimum building operation and maintenance costs associated with various annual operational budgets that ranged from $165K to $300K and for a study period of 20 years. The model is designed to generate an action report of maintenance and upgrade interventions that include detailed recommendations on the building components and equipment repair, replacement, and upgrade for each year in the study period.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Austin, D. (2012). Addressing Market Barriers to Energy Efficiency in Buildings. (February 2010).
Bertone, E., Stewart, R. A., Sahin, O., Alam, M., Zou, P. X. W., Buntine, C., and Marshall, C. (2018). “Guidelines, barriers and strategies for energy and water retrofits of public buildings.” Journal of Cleaner Production, Elsevier Ltd, 174, 1064–1078.
Cho, K., and Kim, T. (2021). “Optimized scheduling method for office building renovation projects.” Expert Systems with Applications, Elsevier Ltd, 168(November 2020), 114212.
Farahani, A. (2019). A systematic approach to strategic maintenance and renovation planning in multifamily buildings.
Farahani, A., Wallbaum, H., and Dalenbäck, J. (2019). “The importance of life-cycle based planning in maintenance and energy renovation of multifamily buildings.” Sustainable Cities and Society, Elsevier, 44(June 2018), 715–725.
Grussing, M. N., and Liu, L. Y. (2014). “Knowledge-Based Optimization of Building Maintenance, Repair, and Renovation Activities to Improve Facility Life Cycle Investments.” Journal of Performance of Constructed Facilities, 28(3), 539–548.
Grussing, M. N., and Marrano, L. R. (2007). “Building component lifecycle repair/replacement model for institutional facility management.” Congress on Computing in Civil Engineering, Proceedings, 550–557.
Hutchison, S., Ghafoori, M., Abdallah, M., and Clevenger, C. (2019). “Optimizing selection of building materials and fixtures to reduce operational costs.” Proceedings, Annual Conference - Canadian Society for Civil Engineering.
Khan, F. I., and Haddara, M. M. (2003). “Risk-based maintenance (RBM): A quantitative approach for maintenance/inspection scheduling and planning.” Journal of Loss Prevention in the Process Industries, 16(6), 561–573.
Kim, J., Han, S., and Hyun, C. (2016). “Minimizing Fluctuation of the Maintenance, Repair, and Rehabilitation Cost Profile of a Building.” Journal of Performance of Constructed Facilities, 30(3), 04015034.
Kwon, N., Song, K., Ahn, Y., Park, M., and Jang, Y. (2020). “Maintenance cost prediction for aging residential buildings based on case-based reasoning and genetic algorithm.” Journal of Building Engineering, Elsevier Ltd, 28(August 2019), 101006.
Marzouk, M., Azab, S., and Metawie, M. (2018). “BIM-based approach for optimizing life cycle costs of sustainable buildings.” Journal of Cleaner Production, Elsevier Ltd, 188, 217–226.
Moretti, N., and Re Cecconi, F. (2019). “A cross-domain decision support system to optimize building maintenance.” Buildings, 9(7).
Nägeli, C., Farahani, A., Österbring, M., Dalenbäck, J. O., and Wallbaum, H. (2019). “A service-life cycle approach to maintenance and energy retrofit planning for building portfolios.” Building and Environment, Elsevier, 160(May), 106212.
NASA. (2008). “Reliability-Centered Maintenance Guide For Facilities and Collateral Equipment.” Engineering Maintenance, (September), 472.
Paulo, P., Branco, F., De Brito, J., and Silva, A. (2016). “BuildingsLife - The use of genetic algorithms for maintenance plan optimization.” Journal of Cleaner Production, Elsevier Ltd, 121, 84–98.
Taillandier, F., Fernandez, C., and Ndiaye, A. (2017). “Real Estate Property Maintenance Optimization Based on Multiobjective Multidimensional Knapsack Problem.” Computer-Aided Civil and Infrastructure Engineering, 32(3), 227–251.
USGBC (U.S. Green Building Council). (2018). LEED v4 for Building Operation and Maintenance. U.S. Green Building Council.
Wang, B., and Xia, X. (2015). “Optimal maintenance planning for building energy efficiency retrofitting from optimization and control system perspectives.” Energy and Buildings, Elsevier B.V., 96, 299–308.
Wang, T.-K., and Piao, Y. (2019). “Development of BIM-AR-Based Facility Risk Assessment and Maintenance System.” Journal of Performance of Constructed Facilities, 33(6), 04019068.
Information & Authors
Information
Published In
History
Published online: Mar 7, 2022
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.