What if machines could predict when they are about to fail?
How AI and condition monitoring are transforming the way we build, maintain and improve the machines of tomorrow.
How AI and condition monitoring are transforming the way we build, maintain and improve the machines of tomorrow.
Every day, we trust machines to keep our world moving. Cars carry us across cities, elevators move us safely between floors and bridges connect communities across rivers and highways. But like the human body, these complex systems can develop hidden weaknesses long before the signs become visible. When these problems go undetected, they can lead to costly repairs, unexpected failures and serious safety risks.
Some researchers are pioneering engineering approaches to prevent these failures before they happen. One of them is Dr. Xihui (Larry) Liang, Associate Professor in the Department of Mechanical Engineering at the Price Faculty of Engineering. Professor Liang’s philosophy is clear: find the warning signs before failure occurs.
Liang’s fascination with machinery began during his undergraduate studies, where he found himself asking not only how machines work, but why they fail. That curiosity led him into the field of reliability engineering. After years of research now his work combines advanced sensing technologies, artificial intelligence and mechanical engineering to help industries move from reactive repairs to predictive maintenance.
“Just as a smartwatch can monitor your heart rate and alert you to potential health issues, we're developing smart sensors and artificial intelligence tools that can continuously monitor machinery, detect problems early and predict failures before they happen.”
Instead of waiting for equipment to break or relying on fixed maintenance schedules, his research allows engineers to monitor a machine’s condition in real time. By recording condition-monitoring signals such as vibrations, acoustics and other operational data, his team uses advanced analysis and AI to detect subtle changes that indicate wear or damage long before a failure occurs.
Professor Liang’s research is already making a difference through collaborations with industry partners across Canada. His team is working with StandardAero to monitor the health of dynamometer bearings used during aircraft engine testing, helping improve reliability in the aerospace sector. In another project, they partnered with ENMAX to monitor wind turbine gearboxes, supporting more dependable renewable energy systems. Closer to home, they are collaborating with the City of Winnipeg to monitor wastewater pumps, critical infrastructure that communities rely on every day.
Liang is also passionate about mentoring the next generation of innovators. He works closely with undergraduate and graduate students who contribute to multitude of areas such as experimental testing and software development. His area of research also directly enhances his teaching where he incorporates real world case studies and emerging technologies to help students connect engineering theory with practical applications. By staying actively involved in industry, Liang ensures his course content remains up to date with evolving industry standards.
Looking ahead, he sees a future where intelligent engineering systems can continuously monitor their own condition, detect problems, predict failures and even support autonomous decision making. His research is increasingly focused on combining advanced sensing technologies, physics based models, digital twins and artificial intelligence to build the next generation of maintenance systems.
One area he is particularly excited about is the development of AI-powered engineering assistants capable of interpreting not just text, but complex engineering data. However, this is not a simple challenge. Training AI systems to understand numerical data and translate it into meaningful insights about the physical condition of equipment requires significant resources, extensive data and advanced engineering knowledge but Liang believes that solving this challenge could fundamentally transform how engineers monitor and manage critical infrastructure around the world.
For Liang, the goal has always been simple: create engineering solutions that are smarter, safer and more sustainable, ensuring the machines we depend on every day continue working when we need them most. Supporting this vision is a strong network of collaborators and funding partners. With support from the University of Manitoba, the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), the National Research Council Canada (NRC), Mitacs, Research Manitoba and industry partners including WestCaRD, StandardAero and other organizations, Liang and his research group continue to advance innovative solutions for a safer, more efficient future.
For nearly 150 years, UM has transformed lives through groundbreaking research and homegrown innovation. We push the boundaries of knowledge and do the hard work here in Manitoba to move our community and the world forward. With a spirit of determination and discovery, we are shaping a better future for our province and beyond.
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