Optimising asset management of community buildings

Keshavarzrad, P 2015, Optimising asset management of community buildings, Masters by Research, Civil, Environmental and Chemical Engineering, RMIT University.

Document type: Thesis
Collection: Theses

Attached Files
Name Description MIMEType Size
Keshavarzrad.pdf Thesis application/pdf 6.67MB
Title Optimising asset management of community buildings
Author(s) Keshavarzrad, P
Year 2015
Abstract Local government agencies in Australia manage around 140,000 community buildings which provide essential services to the community. These are low- to medium- rise structures which often have varying functional requirements and usage. Building assets are the second largest asset group managed by local government. Efficient management of these assets requires understanding of the deterioration of building components, identifying effective condition monitoring methods, forecasting deterioration and the resulting maintenance expenditure, and decision-making considering risk, cost and sustainability throughout the life cycle of the assets. The current approach adopted by most councils is reactive decision-making based on condition data collected at a given point of time.

Due to the large number of components forming a building, deterioration prediction for buildings can be complex. For example, the IPWEA publication NAMS (National Asset Management Strategy, 2009) uses a building hierarchy with 320 inspectable components for defining community buildings. Deterioration prediction of a building requires understanding of the deterioration of the components of buildings and the resultant effect on a complete building. This research presents a method of deriving building component deterioration curves using NAMS (2009) useful lives, percentage change in condition, and a five-level condition rating scheme adopted based on visual inspections. Using the proposed method, basic deterioration curves have been derived for 320 building components defined in NAMS using the reliability-based Markov Process. The curves were then validated using the condition data collected by a local council in Melbourne. In the next stage, relationships between deterioration trends and depreciation of the value of components were derived using data collected from local councils. Since the research focused on analysing deterioration trends at a component level, a facility condition index, which defines the overall building condition as a function of the condition of components, was developed. Furthermore, collected data, deterioration curves and cost templates were converted into an algorithm which was incorporated in the software tool CAMS developed by RMIT Civil Engineering.
Degree Masters by Research
Institution RMIT University
School, Department or Centre Civil, Environmental and Chemical Engineering
Subjects Infrastructure Engineering and Asset Management
Stochastic Analysis and Modelling
Building Construction Management and Project Planning
Community Planning
Keyword(s) Asset management
Deterioration prediction
Depreciation of value
Facility condition assessment
Facility condition index
Version Filter Type
Access Statistics: 221 Abstract Views, 526 File Downloads  -  Detailed Statistics
Created: Wed, 11 May 2016, 09:44:25 EST by Keely Chapman
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us