Presented at the International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT2017), Tokat, Turkey, Dec 02, 2017

SETSCI Conference Proceedings, 2017, 1, Page (s): 322-325 , https://doi.org/

Published Date: 08 December 2017    | 1168     7

Nowadays, competition in industrial production has come to the top with technological improvements. In this competitive environment, producers need better quality, faster and less costly production methods. So, the use of industrial robotic systems is becoming increasingly widespread for different sectors. In this experimental study, the advantages of robot welding automation compared to manual welding process were analyzed. Particularly, the difference between the two processes in the welding trajectory is constantly changed, is revealed as a result of the tests. In this study, Kuka KR6 industrial robot manipulator is used for experimental welding process.

Finally, according to result of the experiment, the welded workpieces obtained from the robotic welding process and the operator manual based welded workpieces are compared. The quality difference between two processes is better observed because the frequency of the trajectory changes frequently in the weld seam in the square wave form. In order to better evaluate the results of this work, the resulting parts were subjected to a tensile test in a laboratory environment. The test results showed that robotic based welding has superior performance for joint two steel plates.  

Keywords - Robotic arc welding, Industrial Robots, Mechatronics System, Automation

[1] X.Z. Chen, S.B. Chen, “The autonomous detection and guiding of start welding position for arc welding robot,” Industrial Robot: An International Journal, vol. 37, pp. 70-78, 2010

[2] H.N.M. Shah, M. Sulaiman, A.Z. Shukor, M.Z.A. Rashid, “Recognition of butt welding joints using background subtraction seam path approach for welding robot,” International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS, vol. 17, pp. 57-62, Feb. 2017.

[3] K. Micallef, G. Fang, M. Dinham, “Automatic seam identification and path planning in robotic welding,” Robotic Welding Intelligence and Automation, vol. 88, pp. 23-32, 2011

[4] M. Dinham, G. Fang, “Autonomous weld seam identification and localisation using eye-in-hand stereo vision for robotic arc welding,” Robotics and Computer-Integrated Manufacturing, vol. 29, pp. 288- 301. 2013.

[5] S. Kim, J.k. Son, S.H. Lee, Prasad K.D.V. Yarlagadda, “Optimal design of neural networks for control in robotic arc welding,” Robotics and Computer-Integrated Manufacturing, vol. 20, pp. 57-63, 2004.

[6] I. Eski, S. Erkaya, S. Savas, S. Yildirim, “Fault detection on robot manipulators using artificial neural networks,” Robotics and Computer-Integrated Manufacturing, vol. 27, pp. 115-123, 2011.

[7] Ş. Yıldırım, B. Ulu, “Design of artificial neural network predictor for trajectory planning of an experimental 6 DOF robot manipulator” in Proc. METRAPP’17, 2017, vol. 52, p. 153.

[8] F. Sanfilippo, L. I. Hatledal, H. Zhang, M. Fago, K. Y. Pettersen, “JOpenShowVar: an open-source cross-platform communication interface to kuka robots,” in Proc. ICIA’14, 2014, p. 1154.