Development of Intelligent Linear Axis Digital Twin for Health Condition Monitoring

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This research project involves a partnership among the Intelligent Control and Estimation (ICE) Laboratory (Dr. Gadsden) at the University of Guelph (Guelph, Ontario), Ford Motor Company of Canada (Windsor, Ontario), and Patti Engineering (Auburn Hills, Michigan, USA). The primary goal of the collaborative research partnership is to develop and apply novel artificial intelligence (AI) and estimation theory techniques to improve the condition monitoring of manufacturing systems. Monitoring the health of manufacturing systems will improve overall part quality, reduce manufacturing downtime, and minimize unscheduled maintenance. The potential outcomes and impacts include: 1) development of new algorithms and techniques based on AI strategies and new estimation methods; 2) development of condition monitoring strategies for improved reliability and safety of manufacturing systems; 3) development of new integration software and techniques for interconnecting manufacturing systems; 4) possibility to translate research discoveries in the public and private sectors, which will lead to socio-economic benefits for Canada; and, 5) training of High Quality Personnel (HQP) as future leaders and employees in the AI and manufacturing fields.