Abstract
Abstract Decisions for building maintenance require integration of various types of information and knowledge created by different members of construction teams such as: maintenance records, work orders, causes and knock-on effects of failures, etc. Failing to capture and use this information/knowledge results in significant costs due to ineffective decisions. Majority of the current building maintenance systems mainly focus on capturing either information or knowledge. This research aims to develop an integrated system to capture information and knowledge of building maintenance operations when/after maintenance is carried out to understand how a building is deteriorating and to support preventive/corrective maintenance decisions. To develop the system, a number of case studies were investigated and interviews were conducted with professionals from different building maintenance departments in public organisations. This methodology helped identify the building maintenance process and the opportunities for knowledge capture and exchange. A taxonomy for building maintenance was then identified which enabled a formal approach for knowledge capture. The proposed system utilises the functions of information modelling techniques and knowledge systems to facilitate full retrieval of information and knowledge for maintenance work. The system consists of two modules; BIM module to capture relevant information and Case-Based Reasoning (CBR) module to capture knowledge. The system can help maintenance teams learn from previous experience and trace the full history of a building element and all affected elements by previous maintenance operations. It is concluded that the integrated knowledge-based BIM systems can provide advanced useful functions for construction operations. On the other hand, incorporating Knowledge Management principles embedded in CBR systems with Information Management principles embedded in BIM systems is a way forward for the transformation from ‘Building Information Modelling’ to ‘Building Knowledge Modelling’.
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