Development of Intelligent Linear Axis Digital Twin for Health Condition Monitoring
开发用于健康状况监测的智能线性轴数字孪生
基本信息
- 批准号:561511-2020
- 负责人:
- 金额:$ 7.17万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Alliance Grants
- 财政年份:2022
- 资助国家:加拿大
- 起止时间:2022-01-01 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
该研究项目涉及圭尔夫大学(安大略省圭尔夫)的智能控制和估计(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)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测。监控制造系统的健康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。潜在的结果和影响包括:1)基于人工智能策略和新的估计方法的新算法和技术的发展;2)制定状态监测策略,以提高制造系统的可靠性和安全性;3)开发用于互联制造系统的新型集成软件和技术;4)将研究发现转化为公共和私营部门的可能性,这将为加拿大带来社会经济效益;5)培养高素质人才(HQP),使其成为人工智能和制造业领域的未来领导者和员工。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Gadsden, StephenAndrewSA其他文献
Gadsden, StephenAndrewSA的其他文献
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{{ truncateString('Gadsden, StephenAndrewSA', 18)}}的其他基金
Development and application of robust estimation and artificial intelligence strategies on noisy and unreliable data
针对噪声和不可靠数据的鲁棒估计和人工智能策略的开发和应用
- 批准号:
566259-2021 - 财政年份:2022
- 资助金额:
$ 7.17万 - 项目类别:
Alliance Grants
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