Robotic friction stir welding

Author(s):  
George E. Cook ◽  
Reginald Crawford ◽  
Denis E. Clark ◽  
Alvin M. Strauss
Author(s):  
Axel Fehrenbacher ◽  
Christopher B. Smith ◽  
Neil A. Duffie ◽  
Nicola J. Ferrier ◽  
Frank E. Pfefferkorn ◽  
...  

Use of robotic friction stir welding (FSW) has gained in popularity as robotic systems can accommodate more complex part geometries while providing high applied tool forces required for proper weld formation. However, even the largest robotic FSW systems suffer from high compliance as compared to most custom engineered FSW machines or modified computer numerical control (CNC) mills. The increased compliance of robotic FSW systems can significantly alter the process dynamics such that control of traditional weld parameters, including plunge depth, is more difficult. To address this, closed-loop control of plunge force has been proposed and implemented on a number of systems. However, due to process parameter and condition variations commonly found in a production environment, force control can lead to oscillatory or unstable conditions and can, in extreme cases, cause the tool to plunge through the workpiece. To address the issues associated with robotic force control, the use of simultaneous tool interface temperature control has been proposed. In this paper, we describe the development and evaluation of a closed-loop control system for robotic friction stir welding that simultaneously controls plunge force and tool interface temperature by varying spindle speed and commanded vertical tool position. The controller was implemented on an industrial robotic FSW system. The system is equipped with a custom real-time wireless temperature measurement system and a force dynamometer. In support of controller development, a linear process model has been developed that captures the dynamic relations between the process inputs and outputs. Process validation identification experiments were performed and it was found that the interface temperature is affected by both spindle speed and commanded vertical tool position while axial force is affected primarily by commanded vertical tool position. The combined control system was shown to possess good command tracking and disturbance rejection characteristics. Axial force and interface temperature was successfully maintained during both thermal and geometric disturbances, and thus weld quality can be maintained for a variety of conditions in which each control strategy applied independently could fail. Finally, it was shown through the use of the control process model, that the attainable closed-loop bandwidth is primarily limited by the inherent compliance of the robotic system, as compared to most custom engineered FSW machines, where instrumentation delay is the primary limiting factor. These limitations did not prevent the implementation of the control system, but are merely observations that we were able to work around.


Author(s):  
Jeroen De Backer ◽  
Gunnar Bolmsjö

Purpose – This paper aims to present a deflection model to improve positional accuracy of industrial robots. Earlier studies have demonstrated the lack of accuracy of heavy-duty robots when exposed to high external forces. One application where the robot is pushed to its limits in terms of forces is friction stir welding (FSW). This process requires the robot to deliver forces of several kilonewtons causing deflections in the robot joints. Especially for robots with serial kinematics, these deflections will result in significant tool deviations, leading to inferior weld quality. Design/methodology/approach – This paper presents a kinematic deflection model, assuming a rigid link and flexible joint serial kinematics robot. As robotic FSW is a process which involves high external loads and a constant welding speed of usually below 50 mm/s, many of the dynamic effects are negligible. The model uses force feedback from a force sensor, embedded on the robot, and predicts the tool deviation, based on the measured external forces. The deviation is fed back to the robot controller and used for online path compensation. Findings – The model is verified by subjecting an FSW tool to an external load and moving it along a path, with and without deviation compensation. The measured tool deviation with compensation was within the allowable tolerance for FSW. Practical implications – The model can be applied to other robots with a force sensor. Originality/value – The presented deflection model is based on force feedback and can predict and compensate tool deviations online.


2018 ◽  
Vol 51 (11) ◽  
pp. 728-733 ◽  
Author(s):  
K. Kolegain ◽  
F. Leonard ◽  
S. Zimmer-Chevret ◽  
A. Ben Attar ◽  
G. Abba

2013 ◽  
Vol 15 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Edward F. Shultz ◽  
Axel Fehrenbacher ◽  
Frank E. Pfefferkorn ◽  
Michael R. Zinn ◽  
Nicola J. Ferrier

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