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.

References

References
1.
Cook
,
G.
,
Crawford
,
R.
,
Clark
,
D.
, and
Strauss
,
A.
, 2004, “
Robotic Friction Stir Welding
,”
Ind. Robot
,
31
(
1
), pp.
55
63
.
2.
Cook
,
G.
,
Smartt
,
H.
,
Mitchell
,
J.
,
Strauss
,
A.
, and
Crawford
,
R.
, 2003, “
Controlling Robotic Friction Stir Welding
,”
Weld. J. (London)
,
82
, pp.
28
34
.
3.
Smith
,
C.
, 2000, “
Robotic Friction Stir Welding Using a Standard Industrial Robot
,”
2nd Friction Stir Welding International Symposium
,
Gothenburg, Sweden
.
4.
Soron
,
M.
, and
Kalaykov
,
I.
, 2006, “
A Robot Prototype for Friction Stir Welding
,”
Robotics, Automation and Mechatronics, 2006 IEEE Conference
, pp.
1
5
.
5.
Zhao
,
X.
,
Kalya
,
P.
,
Landers
,
R.
, and
Krishnamurthy
,
K.
, 2007, “
Design and Implementation of a Nonlinear Axial Force Controller for Friction Stir Welding Processes
,”
Proceedings of the 2007 American Control Conference
, pp.
5553
5558
.
6.
Ogata
,
K.
,
2002,
Linear Control Theory
,
4th ed.
,
Pearson Prentice Hall
, pp.
681
723
.
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