Implementing Proactive Building Asset Management Through Deterioration Prediction: A Case Study in Australia

Wenkai Luo, Guomin Zhang (), Huu Dung Tran, Sujeeva Setunge and Lei Hou
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Wenkai Luo: RMIT University
Guomin Zhang: RMIT University
Huu Dung Tran: RMIT University
Sujeeva Setunge: RMIT University
Lei Hou: RMIT University

A chapter in Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, 2021, pp 951-965 from Springer

Abstract: Abstract Buildings are critical assets in most owner’s asset packages. Maintaining and rehabilitating buildings under various constraints is a crucial challenge for most owners due to the complexity of building components and the uncertainty of their deteriorations. The Markov process based probabilistic approach is an effective solution to develop an asset deterioration prediction model helping owner implementing proactive building asset management. This paper takes one Australian city council as an example to discuss the benefits of an asset deterioration prediction model to the proactive building management and explain how to calibrate and validate the Markov transition matrices from the chronologic discrete assets condition datasets. Two identical findings are that curves derived from the short-period dataset are steeper than that from the long-period dataset, and C2, C3 curves derived from the short-period dataset are not significant.

Keywords: Deterioration prediction; Asset management; Case study (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-8892-1_67

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DOI: 10.1007/978-981-15-8892-1_67

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