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Paper w78-1999-2677:
Information analysis for roofing systems maintenance management integrated system

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Hassanain M A, Froese T M, Vanier D J

Information analysis for roofing systems maintenance management integrated system

Abstract: The Building Envelope Life Cycle Asset Management (BELCAM) project, lead by the National Research Council Canada (NRCC) and Public Works and Government Service Canada (PWGSC), is a "proof of concept" project aimed at helping asset managers to predict the remaining service life of building envelope components and to maximize the return on their maintenance expenditure. The BELCAM project focuses on flat or lowslope conventional roofing systems as a representative domain. This paper focuses on maintenance management, which is primarily concerned with the management of all technical and administrative tasks involved in maintaining a building element in, or restoring it to, a state in which it can perform its intended function. A framework for the integration of the process of managing maintenance of roofing systems is proposed. The framework consists of five sequential steps: (1) Identification of roofing system components requiring assessment, (2) Identification of roofing system performance requirements, (3) Identification of performance assessment methods, (4) Roofing system maintenance planning, (5) Roofing system maintenance operations management. This paper introduces a framework for roofing systems maintenance management. It presents a preliminary analysis of an integrated information system to support maintenance management. The paper follows the development methodology adopted by the International Alliance for Interoperability (IAI) to represent the high-level information within the proposed framework of maintenance management. IAI projects follow a standard process-oriented development methodology, involving the following steps: usage scenarios, process definitions, information analysis and information modeling and validation.



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Series: w78:1999 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.processing (0.013504) class.represent (0.012912) class.analysis (0.011741)
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Permission to reproduce these papers has been graciously provided by the Research Press of the National Research Council of Canada. The support of the editors, particularly Dr. Dana Vanier, is gratefully appreciated.


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