Smart robotic system for advanced manufacturing

先进制造智能机器人系统

• 批准号: 561037-2020
• 负责人: Lee, Jihyun
• 金额: $ 3.64万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=721848
• 关键词: Smart; robotic; system; advanced; manufacturing

With the advent of Industry 4.0, industrial robots are the critical elements of advanced manufacturing. They provide the benefits of space flexibility, long reach, multiple degrees of freedom, and the ability to quickly complete repetitive tasks at a low cost. Manufacturing industries for agriculture, shipping, automotive, aerospace, and oil and gas have begun to use robots to load and unload, deliver, and assemble parts. By collaborating with humans, robots can improve the efficiency in manufacturing and assembling. Robotic application, however, is still restricted to tasks that require low loads because of the robot's low structural rigidity. This low structural stiffness causes vibrations when the robot moves or cuts, which extends the processing time and reduces the finish quality of machined surfaces. Large robots with high rigidity cannot cooperate with humans because they must operate within hard barriers for safety reasons. Sensors can improve the robot's accuracy and safety but their limited types, sizes and high prices pose challenges. The goal of this research project is the development of smart robotic systems to automate manufacturing processes for large, complex structures made of various materials. The novelties lie in technologies to develop a cable-assisted robotic system, a digital model including a robot's kinematics and dynamics, and embedded nano-composite force sensors. The first outcome will be a robotic system with more than a fivefold increase in rigidity, which expands robots' application to machining as well as pick-and-place or metallic 3D printing. The second outcome will be a digital twin model capable of predicting the robots' performance, which can be used to improve the tool path or machining condition. The last outcome will be low-cost embedded sensors with high accuracy and high sensitivity, which can improve safety by making it stop immediately when a human touches it. The completeness of this project will help build partnerships and explore future commercialization paths by generating intellectual properties. This project will train HQP in robotics, manufacturing, and mechatronics for Canada's future industries.

随着工业4.0的到来，工业机器人是先进制造业的关键要素。它们具有空间灵活性、可触及范围长、多自由度以及以低成本快速完成重复任务的能力等优点。农业、航运、汽车、航空航天、石油和天然气等制造业已经开始使用机器人装卸、运送和组装零部件。通过与人类合作，机器人可以提高制造和组装的效率。然而，由于机器人的结构刚度较低，机器人的应用仍然局限于需要低负荷的任务。这种低结构刚度在机器人移动或切割时引起振动，从而延长了加工时间并降低了加工表面的光洁度。高刚性的大型机器人由于安全原因必须在坚硬的障碍物内操作，因此无法与人类合作。传感器可以提高机器人的准确性和安全性，但它们有限的类型、尺寸和高昂的价格构成了挑战。该研究项目的目标是开发智能机器人系统，以实现由各种材料制成的大型复杂结构的自动化制造过程。创新之处在于开发缆索辅助机器人系统的技术，包括机器人运动学和动力学的数字模型，以及嵌入式纳米复合力传感器。第一个成果将是一个刚性增加五倍以上的机器人系统，这将扩大机器人在加工、拾取和金属3D打印方面的应用。第二个结果将是能够预测机器人性能的数字孪生模型，可用于改善刀具轨迹或加工条件。最后一个成果将是低成本的嵌入式传感器，具有高精度和高灵敏度，当人类触摸它时，它可以立即停止，从而提高安全性。该项目的完备性将有助于建立伙伴关系，并通过产生知识产权探索未来的商业化道路。该项目将为加拿大未来的工业培训HQP的机器人、制造和机电一体化。