Development of Intelligent Linear Axis Digital Twin for Health Condition Monitoring

该研究项目涉及Guelph大学(安大略省Guelph)的智能控制和评估(ICE)实验室(Gadsden博士)、加拿大福特汽车公司(安大略省温莎)和Patti Engineering(美国密歇根州奥本山)之间的合作伙伴关系。合作研究伙伴关系的主要目标是开发和应用新的人工智能(AI)和估计理论技术，以改善制造系统的状态监控。监控制造系统的运行状况将提高整体零件质量，减少制造停机时间，并最大限度地减少计划外维护。潜在的成果和影响包括：1)基于人工智能战略和新的估计方法开发新的算法和技术；2)为提高制造系统的可靠性和安全性开发状态监测战略；3)开发用于互联制造系统的新的集成软件和技术；4)将公共和私营部门的研究发现转化为加拿大的社会经济效益；以及5)培训高素质人员(HQP)，使其成为人工智能和制造领域未来的领导者和员工。

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.