AI-based Magnetic Levitation Platform for Smart Manufacturing

基于AI的智能制造磁悬浮平台

• 批准号: RGPIN-2022-03192
• 负责人: Khamesee, MirBehrad
• 金额: $ 1.97万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 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: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760426
• 关键词: AI; based; Magnetic; Levitation; Platform

Many manufacturing and assembly facilities need large spaces for transporting materials between working stations using traditional conveyor systems, and employ pick-and-place robots to position objects within each working station. This is the best current automation in industry where the global industrial automation market is projected to reach $306.2 Billion USD by 2027 (Meticulous Market Research Ltd., March 2021). Magnetic levitation (Maglev) technology, combined with artificial intelligence (AI), can revolutionize industrial automation. The current best practices will be significantly improved by the proposed research program to develop an AI-based magnetic levitation platform for smart manufacturing. The Maglev platform consists of arrays of electromagnetic coils hidden in a pit under the floor. The system can levitate multiple magnetic carriers at the same time, producing fast motions to independently transport objects with instant directional change, which traditional conveyor systems and wheeled carts are not able to achieve. The industrial automation market can benefit from faster productions, smaller factory spaces, and lower carbon footprints. This research program will make the following major contributions in fundamental sciences in robotics, mechatronics, Maglev, and electromechanical systems: a)As a long-term objective, a novel Maglev platform will be developed to anticipate the future needs in the ever-evolving smart manufacturing industry. This system design will be based on significant theoretical and finite element analyses, and electromagnetic systems design. b)Research on modeling of Maglev carriers for optimizing magnetic energy, reducing leakage flux with advanced magnetic circuit designs, and increasing the levitation gap which is a current drawback in using the Maglev systems. c)Research on AI and data driven techniques to enable levitation of multi-carriers to move rapidly without colliding, and minimizing energy consumption and lead time. d)Laser displacement sensors and Machine Learning will be applied to improve the vision system resolution, and to solve the problem of accidental camera vision blockage. This will have a significant impact in the robotic industry as AI vision systems for motion control are becoming increasingly popular. e)As a first-of-its-kind in a collaborative robotics theme, force-controlled collaborative manipulation will be realized using levitated multi-carriers to manipulate the same object to produce a larger payload capacity. Eleven trainees will be trained in mechatronics, robotics, Maglev, systems integration, and automation, i.e., a high-demand engineering expertise in Canada that is desperately in need of trained personnel. This research will contribute to the growth and advancement of the Canadian technology sectors in automotive, electronics, software, and manufacturing industries, and to the economic enhancement of Canada.

许多制造和装配设施需要大的空间来使用传统的输送机系统在工作站之间运输材料，并且采用拾取和放置机器人来将物体定位在每个工作站内。这是目前工业自动化领域最好的情况，预计到2027年全球工业自动化市场将达到3062亿美元（Meidong Market Research Ltd.，二零二一年三月）。磁悬浮（Maglev）技术与人工智能（AI）相结合，可以彻底改变工业自动化。目前的最佳实践将通过拟议的研究计划得到显着改善，以开发用于智能制造的基于人工智能的磁悬浮平台。磁悬浮平台由隐藏在地板下的坑中的电磁线圈阵列组成。该系统可以同时悬浮多个磁性载体，产生快速运动，以独立地运输具有瞬时方向变化的物体，这是传统的输送系统和轮式推车无法实现的。工业自动化市场可以从更快的生产、更小的工厂空间和更低的碳足迹中受益。该研究计划将在机器人，机电一体化，磁悬浮和机电系统的基础科学方面做出以下主要贡献：a）作为一个长期目标，将开发一种新型的磁悬浮平台，以预测不断发展的智能制造业的未来需求。该系统设计将基于重要的理论和有限元分析以及电磁系统设计。B）研究磁悬浮载体的建模，以优化磁能，用先进的磁路设计减少漏磁通，并增加悬浮间隙，这是使用磁悬浮系统的当前缺点。 c）研究人工智能和数据驱动技术，使多载体悬浮快速移动而不会发生碰撞，并最大限度地减少能源消耗和交付时间。d）将应用激光位移传感器和机器学习来提高视觉系统的分辨率，并解决意外相机视觉阻塞的问题。这将对机器人行业产生重大影响，因为用于运动控制的AI视觉系统越来越受欢迎。e）作为协作机器人主题中的首创，力控协作操作将使用悬浮多载体来操纵同一物体以产生更大的有效载荷容量。11名学员将接受机电一体化、机器人、磁悬浮、系统集成和自动化方面的培训，即，在加拿大，这是一个高需求的工程专业知识，迫切需要训练有素的人员。这项研究将有助于加拿大汽车，电子，软件和制造业技术部门的增长和进步，以及加拿大的经济发展。