Large contractors have increasingly depended on various automation techniques and computer information systems facilitating the daily tasks of equipment tracking, maintenance, repair, deployment, and utilization in the last decade. However the current computerized equipment management systems largely focus on book-keeping and data crunching functions, with a lack of support for turning large amounts of collected equipment data into actionable information and knowledge for decision support in equipment management. the speaker will represent the research which aims to improve the current computerized equipment management system through need-based interactive information retrieval as well as automated knowledge generation and exploitation. The issues include design and implementation of a conceptual “equipment data warehouse” to meet the information needs in equipment management; catering for the specific features of construction data in data mining and knowledge generation; design and implementation of intelligent data mining modules in information system to automate the decision support process. The proposed framework for intelligent equipment management is demonstrated through a prototype decision support system developed for a heavy construction contractor in Alberta, Canada.

Speaker
Mr. Hongqin Fan from the Department of Civil and Environmental Engineering at the University of Alberta, Canada.