Clarence de Silva

Canada Research Chair in Mechatronics and Industrial Automation

Tier 1 - 2008-10-01
The University of British Columbia
Natural Sciences and Engineering


Research involves

Monitoring, fault diagnosis, control, and automated design of machinery and industrial processes

Research relevance

Unifying machine health monitoring with control and automated generation of design improvements, leading to significant improvements in performance and safety of the work environment

A Paradigm Shift in Machine Health Monitoring

Machine health monitoring involves the prediction, detection and diagnosis of malfunctions in engineering systems and machines. Machine control — the adjustment of input signals to a machine in order to realize a specified performance —has traditionally involved a separate process.

As the Canada Research Chair in Industrial Automation, Dr. Clarence de Silva addresses the important problem of machine health monitoring from a fresh viewpoint, in the backdrop of the latest developments in sensor technologies, information and communication technologies, intelligent control, machine learning and soft computing.

de Silva’s goal is to develop a unified framework for industrial systems and machinery that will integrate health monitoring with intelligent supervisory control. This technology will enable the online and automated evolution of design improvements through a networked operation from a remote location. This work will lead to significant improvements in product/service quality, productivity, cost, resource requirements, energy efficiency, safety and quality of the work environment and the sustainability of engineering systems.

To accommodate the underlying research and technology development, a modern and unique laboratory facility in network-integrated industrial automation has been established at The University of British Columbia. This facility makes it possible to efficiently share common resources for multiple purposes and projects both locally and remotely. Through networked communication, system problems may be resolved even from remote locations, and hazardous production facilities can be isolated from densely populated areas.

Furthermore, engineers, managers, operators and consultants will be able to work together in a coordinated, interactive, and efficient manner to operate more than one facility, and without needing to be physically present at the same location. Online automated evolutionary design will share many of the same tools and technologies of the unified system framework, and will complement the conventional approaches in subsequent stages of design modification and redesign.