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Applications in Automobile Industries
Published in S. S. Nandhini, M. Karthiga, S. B. Goyal, Computational Intelligence in Robotics and Automation, 2023
G. Sathish Kumar, D. Prabha Devi, R. Ramya, P. Rajesh Kanna
Arc welding is otherwise known as robot welding. It is the process in which the mobile robots are involved in fully automating the process of welding. The mobile robots can handle both the weld and the parts involved in that process. Arc welding is a process where two metals are joined using electricity. The purpose of electricity is to create heat to melt the metals. After heating, metals are cooled down which results in a final welded metal.
Robot Applications
Published in David D. Ardayfio, Fundamentals of Robotics, 2020
Robotic welding has been shown proven to offer a threefold increase in productivity. Effective arc time in manual welding is 20 to 30%, whereas in robot welding it can be raised to 75% because the robot works quickly and continuously. All robot welds are identical and have uniformly high quality. It is easier to control the welding sequence to avoid problems with thermal stresses in the material. If any distortion occurs it is generally the same in every workpiece. Since robot programs can be rerun at any time, setup time is reduced with consequent speedup of the flow of work. Using two unit positioners with a separating glare screen enables loading of one table while the robot is welding on the other table.
Performance analysis of object detection algorithms for robotic welding applications in planar environment
Published in International Journal of Computer Integrated Manufacturing, 2023
Abhilasha Singh, V. Kalaichelvi, R. Karthikeyan
Welding is one of the most popular industrial applications and the use of robots for welding applications is one such task of the Industry 4.0 revolution. The use of robots in welding helps to improve efficiency, quality and productivity. The reason for introducing robots in industrial welding is that manual welding causes problems such as arc eyes, visual disturbances, smoke inhalation and heat exposure to workers. Secondly, robots are better suited to deal with such harsh conditions and can easily handle repetitive welding tasks with high precision and reliability. With the advances in computer vision technology and artificial intelligence, intelligent welding has become one of the most important research areas in industrial automation (Sun et al. 2019). In the field of industrial welding, seam tracking is a major problem that still exists and there are many research works in the field of robotic welding and image processing that address the advances and problems in this area (Ma et al. 2019). With the help of vision-based seam tracking technology, conventional robots using teach pendant can be used to overcome the welding problems and improve the quality of welding (Wang et al. 2021). In recent years, the penetration of industrial robots has increased, and automation has driven the development of technology and manufacturing because performance is more accurate and faster than that of a human (Li et al. 2017; Shao, Liu, and Wu 2019; Lei et al. 2021; Yin et al. 2020). In the field of robotic welding, precise welding can be achieved which is not possible by manual methods. However, many problems are still unexplored. First and foremost, autonomous welding is a difficult task due to high illumination intensity, rust, and cracks. In the present situation, complex welding tasks require human intervention to achieve constant force, consistency, and stability of the weld (Gong et al. 2018). These problems can be solved by using artificial intelligence techniques where human-like skills can be imparted to the robots so that they can think like humans (Vo et al. 2011). Therefore, in this work, object recognition using Deep Learning is applied where the regions of interest such as weld seams are extracted from the image, and the identified shapes are classified to enable accurate and stable welding.