Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Indoor climate control in commercial buildings accounts for 13% of the total energy use and 11% of the CO2x000D
emissions in Canada; and, about 30% of the energy used in commercial buildings is wasted due to poorlyx000D
maintained, degraded, and improperly controlled equipment and components. Therefore, data-driven analyticalx000D
tools for building operation and maintenance have the potential to reduce our environmental impact and tox000D
provide comfortable, healthy, and productive indoor environments.x000D
The objective of this research project is to develop algorithms that will benchmark the maintenancex000D
performance of building systems and components through text-mining within work-order managementx000D
systems. Work-orders are the traditional form of information keeping in buildings. The work-orderx000D
management systems contain operators' descriptions of maintenance routines and failure patterns in HVACx000D
systems and their components, albeit as large amorphous documents. Consequently, they are seldom used tox000D
extract information about common HVAC faults and their occurrence frequencies. New algorithms will bex000D
developed to extract useful information from text-mining work-order management systems. The algorithmsx000D
will identify top system and component-level failure modes, develop component level failure rate models, andx000D
introduce failure modes and effects analysis tools for building systems and their components.x000D
The proposed research project will make significant intellectual, environmental, economic, and HQPx000D
contributions to Canada. New datasets and methods will be created. Adoption of these methods by the industryx000D
partner, Canada's largest property manager Bentall Kennedy, will contribute to our knowledge-based economy.x000D
Wider usage of the algorithms developed in this research project will reduce the environmental and economicx000D
impact of commercial buildings. The HQP will work on data from real buildings, learn their systems andx000D
components, and their shortcomings; and conduct interdisciplinary research on building performance andx000D
data-science