Data investigation and analytics development in support of plant maintenance operations planning

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Major industrial facilities act as the pillars to sustain the quality of life, drive economic developments and also play a pivotal part in improving social and environmental sustainability in Alberta, and in Canada at large. Data-driven, analytical decision support for planning shutdown and maintenance projects on those facilities is vitally important. Improving reliability and predictability in developing maintenance and repair programs for major equipment operation as well as the operation of the entire production system is crucial to strategic competitiveness of the Canadian industry. The proposed ENGAGE project is intended to develop and implement data-driven quantitative techniques to improve current practices so as to enable plant operators to predict potential failures and plan for proper maintenance operations in a more scientific and proactive fashion. The goal is to identify hidden patterns and complex relationships from the historical data so as to lend analytical decision support in planning maintenance operations with higher reliability, efficiency, and cost-effectiveness. The majority of the research (including data analysis, algorithm development and testing) will be performed by the PI's team at University of Alberta. The partner company (Kearl Plant Maintenance Crew, Imperial Oil Ltd.) will facilitate the collection of related information and data from the site and provide technical know-how on major equipment, sensors, and plant operations and maintenance practices. This ENGAGE project will contribute to broadening the scope and impact of Construction Engineering and Management (CEM) research programs at U of A and other major Canadian universities. As such, CEM is not limited to the design and construction phases, but to encompass the operations and maintenance phase in the full life cycle of a major capital project. This is also conducive to having all the stakeholders on board to implement emerging technologies and apply scientific approaches for better project management. ****************