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Condition monitoring and condition aggregation for optimised decision making in management of buildings

journal contribution
posted on 2024-11-01, 15:48 authored by Hessam Mohseni, Sujeeva SetungeSujeeva Setunge, Guomin ZhangGuomin Zhang, Ronald WakefieldRonald Wakefield
Buildings are one of the major infrastructure investments in cities. Sustainable preservation of building assets in order to deliver an appropriate level of service throughout their life cycle requires a comprehensive and optimised decision making methodology. This decision making method needs to be supported not only by accurate data, but also by proper manipulation and aggregation techniques to target the highest potential longevity of construction materials. Condition monitoring methods help asset managers collect required information about their buildings to make justifiable judgments for maintenance and rehabilitation strategies. This data is collected in the condition monitoring stage within a defined scope of a condition monitoring manual. The level of detail in data collection may depend on the asset management system, element hierarchy adopted by the organization and criticality of assets. While detailed condition data is collected during building condition assessments, for higher-level optimised strategic asset management overall conditions of element groups are desirable to project the capital investments and expenditures. The paper reviews condition monitoring techniques for buildings and also presents a risk-based methodology for aggregating the inspected conditions to a higher group level of inspected elements which leads to a greater accuracy of decisions to be made for strategic management of buildings.

History

Journal

Applied Mechanics and Materials

Volume

438 - 439

Start page

1719

End page

1725

Total pages

7

Publisher

Trans Tech Publications

Place published

Switzerland

Language

English

Copyright

© (2013) Trans Tech Publications, Switzerland

Former Identifier

2006044793

Esploro creation date

2020-06-22

Fedora creation date

2014-05-13

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