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Le, A T H, Domingo, N, Rasheed, E and Park, K S (2018) Building Maintenance Cost Planning and Estimating: A Literature Review. In: Gorse, C and Neilson, C J (Eds.), Proceedings 34th Annual ARCOM Conference, 3-5 September 2018, Queen’s University, Belfast, UK. Association of Researchers in Construction Management, 697–706.
- Type: Conference Proceedings
- Keywords: building maintenance, cost estimating, cost planning, maintenance cost, maintenance management
- ISBN/ISSN: 978-0-9955463-2-5
- URL: http://www.arcom.ac.uk/-docs/proceedings/8c141dae599eb1b711ac2e58792f952a.pdf
- Abstract:
Construction industry is orientated towards sustainable development by introducing advanced technologies, materials, and methods that will both reduce adverse impacts on the environment and use budget effectively. In terms of economic aspect of the sustainability, predicting maintenance cost accuracy in use phase plays a vital role in protecting facility investment in whole-life cost of buildings. Additionally, a better understanding of required maintenance funding will provide opportunities for cost-effective improvement in building performance when upgrading, replacing or refurbishing the buildings. There are different approaches to estimating maintenance costs such as value-based, formula-based, lifecycle-based and condition assessment. The formula-based methodology is considered as the most common one using mathematical expression varying from simple and single variable formula to sophisticated algorithms. The advantage of this method is that variables applied in the formulas tend to both quantifiable physical attributes of the facility inventory such as age and area, as well as unqualifiable attributes such as type, location, function, construction methods and operation strategies. This paper is a part of a research that expects to create a forecasting model for building maintenance cost which will identify relationships between the costs and facility characteristics. To achieve the finding, most widely adopted formula-based estimation models will be critically reviewed. Comparision of these models mainly focuses on methodologies, data collection, data analysis and consequence functions of the models. Recommendations are suggested to develop and complement an appropriate estimation model for future use.