Memorial University DAI: A knowledge-based decision support system in reliability-centered maintenance of HVAC systems

advanced search

Digital Archives Initiative
Memorial University - Electronic Theses and Dissertations 3

menu off

add document to favorites : add page to favorites : reference url

back to results : previous : next

Search this object:

0 hit(s) :: previous hit : next hit

View:

previous page : next page

Document Description

Title	A knowledge-based decision support system in reliability-centered maintenance of HVAC systems
Author	Wong, Daniel, 1949-
Description	Thesis (Ph.D.), Memorial University of Newfoundland, 2000. Engineering and Applied Science
Date	2000
Pagination	xx, 293 leaves
Subject	Buildings--Environmental engineering; Reliability (Engineering)
Degree	Ph.D.
Degree Grantor	Memorial University of Newfoundland. Faculty of Engineering and Applied Science
Discipline	Engineering and Applied Science
Language	Eng
Notes	Bibliography: leaves 174-178
Abstract	Studies have shown that in large physical systems, it is possible to eliminate or reduce costly machine failures, equipment downtime, lost production and decreased revenues by keeping abreast of the most effective and current maintenance techniques available. -- The purpose of this thesis is to propose a multi-faceted approach to maintenance which can address the short comings of conventional approaches to maintenance. -- The proposed methodology combines the reliability-centered maintenance technique (RCM), a fault tree analysis, a database system, and the Weibull analysis. The integration of these techniques produces an innovative system which increases the reliability and availability of the system. To the author's knowledge, this integrated approach has not been done before. -- As an example, the heating, ventilating and air conditioning (HVAC) of large buildings was used to illustrate this methodology. Failure data was collected from the Biotechnology. Arts and Administration Extension and Earth Resources Buildings of Memorial University of Newfoundland (CERR) over a six year period. The data included the time to failure and failure modes for each component within the central HVAC system. The collected data was used to quantify the reliability of the system. A probabilistic analysis based on the Weibull distribution was used to analyze the time to failure data. -- Using reliability-centered maintenance to identify the causes and impact of failures, the information acquired was used to develop fault trees. Failure modes identified in the fault trees were coded as identifiers to be used in a knowledge-based system for improving the reliability and availability of the system and its components. -- It was shown that system reliability can be improved by increasing the reliability of each component utilizing the proposed multi-faceted approach. Failure data analysis enabled us to quantify the reliability for many sub-components within the major components that constitute the HVAC system. -- It is concluded that the developed knowledge-based system enables us to troubleshoot causes of failure at a much faster rate and this will decrease the down time and increase the availability of the svstem.
Type	Text
Resource Type	Electronic thesis or dissertation
Format	Image/jpeg; Application/pdf
Source	Paper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries
Local Identifier	a1477543
Rights	The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
Collection	Electronic Theses and Dissertations
Scanning Status	Completed
PDF File	(25.91 MB) -- http://collections.mun.ca/PDFs/theses/Wong_Daniel.pdf
CONTENTdm file name	141201.cpd