AI-based Magnetic Levitation Platform for Smart Manufacturing

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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.