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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=707099
• 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，工业机器人成为先进制造的关键要素。它们具有空间灵活性、长距离、多自由度以及以低成本快速完成重复性任务的能力等优点。农业、航运、汽车、航空航天、石油和天然气等制造业已开始使用机器人装卸、交付和组装零件。通过与人类协作，机器人可以提高制造和装配的效率。然而，由于机器人的结构刚度较低，机器人的应用仍然仅限于需要低负载的任务。这种较低的结构刚度会导致机器人移动或切割时产生振动，从而延长加工时间并降低加工表面的光洁度质量。具有高刚性的大型机器人无法与人类合作，因为出于安全原因它们必须在坚硬的障碍物内操作。传感器可以提高机器人的准确性和安全性，但其有限的类型、尺寸和高昂的价格带来了挑战。 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制造过程自动化。新颖之处在于开发电缆辅助机器人系统、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的技术。第一个成果将是刚性增加五倍以上的机器人系统，这将机器人的应用扩展到机械加工以及拾放或金属 3D 打印。第二个成果将是能够预测机器人性能的数字孪生模型，可用于改善刀具路径或加工条件。最后的成果将是具有高精度和高灵敏度的低成本嵌入式传感器，当有人触摸它时它可以立即停止，从而提高安全性。该项目的完成将有助于建立合作伙伴关系，并通过产生知识产权来探索未来的商业化路径。该项目将为加拿大未来产业培训机器人、制造和机电一体化领域的总部人员。