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Paper w78-1992-103:
An expert system for strategic maintenance planning

Facilitated by the SciX project

Brandon P, Watson I

An expert system for strategic maintenance planning

Abstract: Recent changes in legislation have made housing associations (HAs) more financially responsible for all aspects of maintenance of their new housing stock. Because of the levels of funding within HAs and the need to provide accommodation at a "fair rent,"the planning of maintenance, and the consequent planning of expenditure has never before been so vital. Moreover, most literature on maintenance, including government reports and research by professional bodies or academic institutions, identifies a need for improvement in decision making regarding building maintenance. The project has provided an expert system (ES) that assists maintenance and finance officers in strategic planning of maintenance. The system (called EMMY) is not a database for HAs building stock and their tenants, or a program that itemises maintenance jobs, handles invoices, and performs various accounting tasks. It is a strategic management tool. Whilethere are many programs in existence that estimate the life-cycle costs of buildings or provide maintenance management, they all share two major problems: They require voluminous data input to describe each building; They function as "black boxes;" that is, data is put in and answers are given with little indication ofhowthe answers were generated and what variables affected the results. Storing all the relevant information in a database and selecting only that information required for the building under consideration is one method of reducing data input. In this way one can construct a modelof the building from pre-packaged components, and calculations can then be performed using spreadsheets. This approach has the advantage ofreducing data input and being relatively low cost (Tuts 89). Althoughthere is avariety of computer software available to the industry, thetechnology with potentially the greatest benefits is still the least known and most rarely used - the ES. ESs can directly address both of the problems outlined above: by reducing t



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Series: w78:1992 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.strategies (0.055604) class.social (0.033963) class.synthesis (0.021859)
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Permission to reproduce these papers has been graciously provided by Research Press of the National Research Council of Canada. The support of the editor, Dr. Dana Vanier, is gratefully appreciated.


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