Yale Software Predicts Maintenance Problems
Technology uses fault-detection algorithms and predictive logic to pinpoint mechanical faults in real-time. January 5, 2024
By Dan Hounsell, Senior Editor
The evolution of technology in institutional and commercial facilities has given front-line maintenance and engineering technicians more power than ever. In a growing number of facilities, they now can detect and diagnose problems with critical systems more quickly and efficiently than ever. Yale University offers one of the most promising applications of facilities technology.
In 2019, the university implemented technology that uses fault-detection algorithms and predictive logic to pinpoint mechanical faults in real-time, saving energy and money and moving the university closer to its goal of net zero emissions by 2035.
The analytics software, referred to as automatic fault detection and diagnostics, processes data from building mechanical systems and energy meters to find problems and identify the root causes, while evaluating the performance of building systems for energy, comfort and maintenance.
Using algorithms and predictive logic, the software can take in information from Yale building systems and energy meters and make judgment calls about whether the systems are performing well. Crucially, it also projects the cost in energy and dollars of not fixing a malfunction, helping Yale’s energy analysts to prioritize the most urgent repairs.
Dan Hounsell is senior editor for the facilities market. He has more than 30 years of experience writing about facilities maintenance, engineering and management.
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