Journal of the Korean Society of Manufacturing Technology Engineers (한국생산제조학회지)

The Korean Society of Manufacturing Technology Engineers (한국생산제조학회)
권호 표지
DOI QR코드

DOI QR Code

Prediction of the Top-bead width of Tandem GMA Welding Processes Using the STACO Model

STACO 모델을 이용한 탄템 GMA 용접공정의 표면비드 폭 예측

  • Lee, Jong Pyo (Department of Machanical Engineering, Mokpo National University) ;
  • Park, Min Ho (Department of Machanical Engineering, Mokpo National University) ;
  • Kim, Do Hyeong (Department of Machanical Engineering, Mokpo National University) ;
  • Jin, Byeong Ju (Department of Machanical Engineering, Mokpo National University) ;
  • Son, Joon Sik (Research Institute of Medium & Small Shipbuilding) ;
  • Kang, Bong Yong (Korea Institute of Industrial Technology) ;
  • Shim, Ji Yeon (Korea Institute of Industrial Technology) ;
  • Kim, Ill Soo (Department of Machanical Engineering, Mokpo National University)
  • Received : 2015.09.17
  • Accepted : 2015.11.30
  • Published : 2016.02.15
Download PDF
⟨ Previous Next ⟩

Abstract

Tandem arc welding is a guarantor for high efficiency and cost saving since the quantity of wire which is deposited in the welding is approximated 30% greater that in conventional welding. The welding process is now being successfully applied in many industries. However, in the case of tandem arc welding, good quality and high productivity should depend on the welding parameters. Therefore, an intelligent algorithms for the automatic tandem arc welding process has been necessarily required. In this study, a predictive model based on the neural network by using the data acquired during tandem gas metal arc (GMA) welding process has been developed. To verify the reliability of the developed predictive model, a mutual comparison with the surface of the top-bead width obtained from actual experiments has been analyzed.

Keywords

References

  1. The Small and Medium Business Administration, 2014, Report on Road-map of Small and Medium Industry on Manufacture Based Integration Technology, 564-564.
  2. Wikle, H. C., Kottilingam, S., Zee, R. H., Chin, B.A.,, 2001, Infrared sensing techniques for penetration depth control of the submerged arc welding process, Journal of Materials Processing Technology, 113 228-233. https://doi.org/10.1016/S0924-0136(01)00587-8
  3. Mulligan, S. J., Melton, G. B.,, 2002, An assessment of the Tandem MIG-MAG welding process, TWI report. 745.
  4. Moon, H. S., Beattie, R. J., 2001, Adaptive multitorch multipass SAW, Journal of KWS, 1 1-7.
  5. Park, S. J., Nam, S. K., Kweon, C. G., 2012, Prediction of Weld Penetration and Deposited Metal Area in Accordance with Weld Parameters in Tandem Submerged Arc Welding Process, KWJS. 39:6 71-26.
  6. Park, T. K., Yang, J. S., Cho, S. M., 2004, Parallel ANOVA Processing, KWJS. 45 141-143.
  7. Poliak, 1986, Wide-Angle-Reflective Cube-corner Retrorective Sheeting, MIT Press Cambridge Mass. 318-362.