Combined Temperature and Force Control for Robotic Friction Stir Welding

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
Axel Fehrenbacher ◽  
Christopher B. Smith ◽  
Neil A. Duffie ◽  
Nicola J. Ferrier ◽  
Frank E. Pfefferkorn ◽  
...  
Keyword(s):  
Control System ◽  
Friction Stir Welding ◽  
Force Control ◽  
Process Model ◽  
Closed Loop ◽  
Interface Temperature ◽  
Friction Stir ◽  
Tool Position ◽  
Robotic Friction Stir Welding ◽  
Robotic Fsw

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.

Combined Temperature and Force Control for Robotic Friction Stir Welding

2013 ◽  
Author(s):  
Axel Fehrenbacher ◽  
Christopher B. Smith ◽  
Neil A. Duffie ◽  
Nicola J. Ferrier ◽  
Frank E. Pfefferkorn ◽  
...  
Keyword(s):  
Control System ◽  
Force Control ◽  
Closed Loop ◽  
Interface Temperature ◽  
Closed Loop Control ◽  
Weld Quality ◽  
Loop Control ◽  
Friction Stir ◽  
Tool Position ◽  
Robotic Friction Stir Welding

The objective of this research is to develop a closed-loop control system for robotic friction stir welding (FSW) that simultaneously controls force and temperature in order to maintain weld quality under various process disturbances. FSW is a solid-state joining process enabling welds with excellent metallurgical and mechanical properties, as well as significant energy consumption and cost savings compared to traditional fusion welding processes. During FSW, several process parameter and condition variations (thermal constraints, material properties, geometry, etc.) are present. The FSW process can be sensitive to these variations, which are commonly present in a production environment; hence, there is a significant need to control the process to assure high weld quality. Reliable FSW for a wide range of applications will require closed-loop control of certain process parameters. A linear multi-input-multi-output process model has been developed that captures the dynamic relations between two process inputs (commanded spindle speed and commanded vertical tool position) and two process outputs (interface temperature and axial force). A closed-loop controller was implemented that combines temperature and force control on an industrial robotic FSW system. The performance of the combined control system was demonstrated with successful command tracking and disturbance rejection. Within a certain range, desired axial forces and interface temperatures are achieved by automatically adjusting the spindle speed and the vertical tool position at the same time. The axial force and interface temperature is 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.

Toward Automation of Friction Stir Welding Through Temperature Measurement and Closed-Loop Control

2011 ◽  
Vol 133 (5) ◽  
Author(s):  
Axel Fehrenbacher ◽  
Neil A. Duffie ◽  
Nicola J. Ferrier ◽  
Frank E. Pfefferkorn ◽  
Michael R. Zinn
Keyword(s):  
Control System ◽  
Friction Stir Welding ◽  
Temperature Measurement ◽  
Closed Loop ◽  
Weld Zone ◽  
Spindle Speed ◽  
Weld Quality ◽  
Friction Stir ◽  
Integral Controller ◽  
Zone Temperature

The objectives of this work are to determine an accurate temperature feedback strategy and to develop a closed-loop feedback control system for temperature in friction stir welding (FSW). FSW is a novel joining technology enabling welds with excellent metallurgical and mechanical properties, as well as significant energy consumption and cost savings. However, numerous parameter and condition variations are present in the FSW production environment that can adversely affect weld quality, which has made extensive automation of this process impossible to date. To enable large scale automation while maintaining weld quality, techniques to control the FSW process in the presence of unknown disturbances must be developed. One process variable that must be controlled to maintain uniform weld quality under the inherent workpiece variability (thermal constraints, material properties, geometry, etc.) is the weld zone temperature. Our hypothesis is that the weld zone temperature can be controlled, which can help in controlling the weld quality. A wireless data acquisition system was built to measure temperatures at the tool-workpiece interface. A thermocouple was placed in a through hole right at the interface of tool and workpiece so that the tip is in contact with the workpiece material. This measurement strategy reveals temperature variations within a single rotation of the tool in real time. In order to automate the system, a first order process model with transport delay was experimentally developed that captures the physics between spindle speed and measured interface temperature. The model has a time constant of 110 ms and a delay time of 85 ms. Using this temperature measurement technique, a closed-loop temperature control system with a bandwidth of 0.3 Hz was developed. Interface temperatures in the range from 555 °C to 575 °C were commanded to an integral controller, which regulated the spindle speed between 850 rpm and 1250 rpm to adjust the heat generation and achieve the desired interface temperatures in 6061-T6 aluminum. To simulate changes in thermal boundary conditions, backing plates of different thermal diffusivities were found to effectively alter the heat flow, hence, weld zone temperature. The integral controller that manipulates spindle speed is applied when welding during these intentionally introduced weld disturbances. The measured temperature stayed within ±5 °C after introducing the disturbance, compared to a 50 °C change in temperature when no control was applied.

The Identification of the Key Enablers for Force Control of Robotic Friction Stir Welding

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
William R. Longhurst ◽  
Alvin M. Strauss ◽  
George E. Cook
Keyword(s):  
Friction Stir Welding ◽  
Force Control ◽  
Weld Seam ◽  
Welding Process ◽  
Tool Geometry ◽  
Work Piece ◽  
Successful Implementation ◽  
Plunge Depth ◽  
Friction Stir ◽  
Robotic Friction Stir Welding

Friction stir welding (FSW) is a solid state welding process that uses a rotating tool to plastically deform and then forge together materials. This process requires a large axial force to be maintained on the tool as the tool is plunged into the work piece and traversed along the weld seam. Force control is required if robots are to be used. Force control provides compensation for the compliant nature of robots. Without force control, welding flaws would continuously emerge as the robot repositioned its linkages to traverse the tool along the weld seam. Insufficient plunge depth would result and cause the welding flaws as the robot’s linkages yielded from the resulting force in welding environment. As FSW continues to emerge in manufacturing, robotic applications will be desired to establish flexible automation. The research presented here identifies the key enablers for successful and stable force control of FSW. To this end, a FSW force controller was designed and implemented on a retrofitted Milwaukee Model K milling machine. The closed loop proportional, integral plus derivative control architecture was tuned using the Ziegler–Nichols method. Welding experiments were conducted by butt welding 0.25 in. (6.35 mm) × 1.50 in. (38.1 mm) × 8.0 in. (203.2 mm) samples of aluminum 6061 with a 0.25 in. (6.35 mm) threaded tool. The experimental force control system was able to regulate to a desired force with a standard deviation of 129.4 N. From the experiments, it was determined that tool geometry and position are important parameters influencing the performance of the force controller, and four key enablers were identified for stable force control of FSW. The most important enabler is the maintaining of the position of a portion of the tool’s shoulder above the work piece surface. When the shoulder is completely submerged below the surface, an unstable system occurs. The other key enablers are a smooth motion profile, an increased lead angle, and positional constraints for the tool. These last three enablers contribute to the stability of the system by making the tool’s interaction with the nonlinear welding environment less sensitive. It is concluded that successful implementation of force control in the robotic FSW systems can be obtained by establishing and adhering to these key enablers. In addition, force control via plunge depth adjustment reduces weld flash and improves the appearance of the weld.

Robotic force control for deburring using an active end effector

Robotica ◽  
1989 ◽  
Vol 7 (4) ◽  
pp. 303-308 ◽  
Author(s):  
G. M. Bone ◽  
M. A. Elbestawi
Keyword(s):  
Control System ◽  
Force Control ◽  
Pid Controller ◽  
Closed Loop ◽  
Least Squares Method ◽  
Closed Loop Control ◽  
End Effector ◽  
Loop Control ◽  
Positioning Errors ◽  
Force Control System

SUMMARYAn active force control system for robotic deburring based on an active end effector is developed. The system utilizes a PUMA-560 six axis robot. The robot's structural dynamics, positioning errors, and the deburring cutting process are examined in detail. Based on ARMAX plant models identified using the least squares method, a discrete PID controller is designed and tested in real-time. The control system is shown to maintain the force within l N of the reference, and reduce chamfer depth errors to 0.12 mm from the 1 mm possible without closed-loop control.

Robotic friction stir welding

2004 ◽  
Vol 31 (1) ◽  
pp. 55-63 ◽  
Author(s):  
George E. Cook ◽  
Reginald Crawford ◽  
Denis E. Clark ◽  
Alvin M. Strauss
Keyword(s):  
Friction Stir Welding ◽  
Friction Stir ◽  
Robotic Friction Stir Welding
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