UWSpace is currently experiencing technical difficulties resulting from its recent migration to a new version of its software. These technical issues are not affecting the submission and browse features of the site. UWaterloo community members may continue submitting items to UWSpace. We apologize for the inconvenience, and are actively working to resolve these technical issues.
 

A Framework for Efficient Condition Assessment of the Building Infrastructure

dc.contributor.authorSingh Ahluwalia, Shipra
dc.date.accessioned2008-10-21T16:20:05Z
dc.date.available2008-10-21T16:20:05Z
dc.date.issued2008-10-21T16:20:05Z
dc.date.submitted2008-10-17
dc.description.abstractCurrently, in North America, a large percentage of infrastructure assets, including education and healthcare buildings, are deteriorating rapidly due to age and over capacity. The budget constraints under which municipalities and public agencies operate also make the sustainability of these buildings a serious challenge. This is particularly so when capital renewal programs are downsized to save money, thus hindering the proper inspection of buildings and the allocation of renewal funds. In addition, building inspections and condition assessments are generally resource intensive, subjective, time-consuming, and costly. To support capital renewal decisions that pertain to buildings, this research introduces a comprehensive condition assessment framework that overcomes the drawbacks of the existing processes. A prototype of the framework utilizing hand-held devices has been developed and tested on the capital renewal program of the Toronto District School Board (TDSB). The framework is innovative on three main fronts: (1) it utilizes available reactive-maintenance records to predict the condition of components and to prioritize inspection tasks among limited available resources; (2) it employs a unique visual guidance system that is based on extensive surveys and field data collection to support uniform condition assessment of building components; and (3) it introduces a location-based inspection process with a standardized building hierarchy. The research contributes to restructuring the inspection and condition assessment processes, providing a better understanding of the interactions among building components, integrating capital renewal and maintenance data, and developing a practical condition assessment framework that is economical, less-subjective, and suitable for use by individuals with less experience. The framework also incorporates permanent documentation of the condition of the asset along its life cycle, and aids in scheduling inspections so as to maintain low-cost condition tracking. Ultimately, the proposed system will provide timely and sufficient information to facilitate accurate repair decisions for maintaining the building infrastructure. The framework is of benefit to both researchers and practitioners. Its formulation is innovative and helps building owners automate most inspection tasks, quantify the impact of alternative funding scenarios, and reduce the cost of asset management. In addition, because asset management is a less-developed multi-billion dollar business, the research is expected to establish leading technology and know-how that will help Canadian companies gain a competitive global advantage. At the municipality level, the proposed prototype is expected to assist managers in arriving at decisions that will ensure the cost-effective operation of buildings and uninterrupted service to the public.en
dc.identifier.urihttp://hdl.handle.net/10012/4093
dc.language.isoenen
dc.pendingfalseen
dc.publisherUniversity of Waterlooen
dc.subjectCondition assessmenten
dc.subjectBuildingsen
dc.subject.programCivil Engineeringen
dc.titleA Framework for Efficient Condition Assessment of the Building Infrastructureen
dc.typeDoctoral Thesisen
uws-etd.degreeDoctor of Philosophyen
uws-etd.degree.departmentCivil and Environmental Engineeringen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Shipra_SA_PhD_Thesis.pdf
Size:
6.06 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
260 B
Format:
Item-specific license agreed upon to submission
Description: