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; 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.

随着行业4.0的出现，工业机器人是高级制造的关键要素。它们提供了空间灵活性，长距离，多个自由度的好处，以及以低成本快速完成重复任务的能力。农业，运输，汽车，航空航天以及石油和天然气的制造业开始使用机器人加载和卸货，交付和组装零件。通过与人类合作，机器人可以提高制造和组装的效率。但是，机器人应用仍然仅限于由于机器人的结构刚度低而需要低负载的任务。当机器人移动或切割时，这种低的结构刚度会引起振动，从而延长了处理时间并降低了加工表面的饰面质量。刚性高的大型机器人不能与人合作，因为出于安全原因，它们必须在硬障碍物内运行。传感器可以提高机器人的准确性和安全性，但其类型有限，尺寸和高价构成挑战。 该研究项目的目的是开发智能机器人系统，以自动化由各种材料制成的大型复杂结构的制造过程。新颖性在于技术开发有线辅助机器人系统的技术，这是一种数字模型，包括机器人的运动学和动力学以及嵌入的纳米复合力传感器。第一个结果将是一个机器人系统，其刚度增加了五倍，它扩大了机器人在加工以及拾取或金属3D打印的应用程序上的应用。第二个结果将是能够预测机器人性能的数字双胞胎模型，该模型可用于改善工具路径或加工条件。最后的结果将是具有高精度和高灵敏度的低成本嵌入式传感器，这可以通过在人类接触时立即停止安全性来提高安全性。该项目的完整性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行业的机器人技术，制造和机电一体化培训HQP。