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Optimization of pulsed GTA welding process parameters for the welding of AISI 304L stainless steel sheets

  • P. K. GiridharanEmail author
  • N. Murugan
ORIGINAL ARTICLE

Abstract

Optimization of pulsed gas tungsten arc welding (pulsed GTAW) process parameters was carried out to obtain optimum weld bead geometry with full penetration in welding of stainless steel (304L) sheets of 3 mm thickness. Autogenuous welding with square butt joint was employed. Design of experiments based on central composite rotatable design was employed for the development of a mathematical model correlating the important controllable pulsed GTAW process parameters like pulse current (I p), pulse current duration (T p), and welding speed (S) with weld bead parameters such as penetration, bead width (W), aspect ratio (AR), and weld bead area of the weld. The developed models were checked for adequacy based on ANOVA analysis and accuracy of prediction by conducting a confirmation test. Weld bead parameters predicted by the models were found to confirm observed values with high accuracy. Using these models, the main and interaction effects of pulsed GTAW process parameters on weld bead parameters were studied and discussed. Optimization of pulsed GTAW process parameters was carried out to obtain optimum bead geometry using the developed models. A quasi-Newton numerical optimization technique was used to solve the optimization problem and the results of the optimization are presented.

Keywords

Pulsed GTAW process Welding of stainless steel sheets Mathematical models Design of experiments ANOVA analysis and optimization 

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References

  1. 1.
    Murugan N, Parmar RS, Sud SK (1993) Effect of submerged arc process parameters on dilution and bead geometry in single wire surfacing. J Mater Process Technol 37:767–780CrossRefGoogle Scholar
  2. 2.
    Cornu J (1988) Advanced welding system, TIG and related processes, vol 3. Springer, Heidelberg, p 61Google Scholar
  3. 3.
    Gunaraj V, Murugan N (2000) Prediction and optimization of weld bead volume for submerged arc process—part 1. Weld J 79(10):286s–294sGoogle Scholar
  4. 4.
    Gunaraj V, Murugan N (2000) Prediction and optimization of weld bead volume for submerged arc process—part 2. Weld J 79(11):294s–331sGoogle Scholar
  5. 5.
    Kim IS, Son JS, Kim IG, Kim JY, Kim OS (2003) A study on relationship between process variables and bead penetration for robotic CO2 arc welding. J Mater Process Technol 136(1–3):139–145CrossRefGoogle Scholar
  6. 6.
    Tarng YS, Yang WH (1998) Optimization of the weld bead geometry in gas tungsten arc welding by the Taguchi method. Int J Adv Manuf Technol 14(8):549–554Google Scholar
  7. 7.
    Abu Aesh M (2001) Optimization of weld bead dimensions in GTAW of aluminum-magnesium alloy. Mater Manuf Process 16(5):725–736CrossRefGoogle Scholar
  8. 8.
    Murugan N, Parmar RS (1994) Effects of MIG process parameters on the geometry of bead in automatic surfacing of stainless steel. J Mater Process Technol 41:381–398CrossRefGoogle Scholar
  9. 9.
    Palani PK, Murugan N (2007) Optimization of weld bead geometry for stainless steel claddings deposited by FCAW. J Mater Process Technol 190(1–3):291–299CrossRefGoogle Scholar
  10. 10.
    Balasubramanian M, Jayabalan V, Balasubramanian V (2007) Process optimization of PC TIG welding of Titanium alloy using the modified Taguchi method. Int J Manuf Res 2(4):403–413CrossRefGoogle Scholar
  11. 11.
    Chen SB, Zhang Y, Qiu T, Lin T (2003) Robotic welding systems with vision sensing and self-learning neuron control of arc welding dynamic process. J Intell Robot Syst 36(2):191–208CrossRefGoogle Scholar
  12. 12.
    Tsai C-H, Hou K-H, Chuang H-T (2006) Fuzzy control of pulsed GTA welds by using real-time root bead image feedback. J Mater Process Technol 176(1–3):158–167CrossRefGoogle Scholar
  13. 13.
    Chen SB, Zhang Y, Lin T, Qiu T, Wu L (2004) Welding robotic systems with visual sensing and real-time control of dynamic weld pool during pulsed GTAW. Int J Robot Autom 206(1)2602–2606Google Scholar
  14. 14.
    Chen SB, Zhao DB, Wu L, Lou YJ (2000) Intelligent methodology for sensing, modeling and control of pulsed GTAW, part II—butt welding. Weld J 79(6):164s–174sGoogle Scholar
  15. 15.
    Chen SB, Zhao DB, Wu L, Lou YJ (2000) Intelligent methodology for sensing, modeling and control of pulsed GTAW, part I—bead-on-plate welding. Weld J 79(6):151s–163sGoogle Scholar
  16. 16.
    Zhao DB, Yi JQ, Chen SB, Wu L (2004) Surface shape reconstruction of weld pool during pulsed GTAW from its single image, lecture notes in control and information sciences, robotic welding, intelligence and automation, vol 299. Springer, Berlin, pp 56–62Google Scholar
  17. 17.
    Lothongkum G, Chaumbai P, Bhandhubanyong P (1999) TIG pulse welding of 304L austenitic stainless steel in flat, vertical and over head position. J Mater Process Technol 89–90:410–414CrossRefGoogle Scholar
  18. 18.
    Lothongkum G, Viyanit E, Bhandhubanyong P (2001) TIG pulse welding parameters of the AISI 316L stainless steel plate at the 6–12h positions. J Mater Process Technol 91–92:312–316Google Scholar
  19. 19.
    Omar AA, Ludin CD (1979) Pulsed plasma—pulsed GTA arc: a study of process variables. Weld J 58(4):97s–105sGoogle Scholar
  20. 20.
    Hames P, Smith BL (1993) Factorial techniques for weld quality prediction. Met Constr 15:128–130Google Scholar
  21. 21.
    Montgomery DC (2005) Design and analysis of experiments, 6th edn. Wiley, New YorkGoogle Scholar
  22. 22.
    Myers RH, Montgomery DC (2002) Response surface methodology, process and product optimization using designed experiments, 2nd edn. Wiley, New YorkGoogle Scholar
  23. 23.
    Giridharan PK, Murugan N (2007) Effect of pulsed gas tungsten arc welding process parameters on pitting corrosion resistance of type 304L stainless steel welds. Corros J 63(5):433–441CrossRefGoogle Scholar
  24. 24.
    Systat (2004) SYSTAT, version 11. Systat Inc., San Jose, CAGoogle Scholar
  25. 25.
    Montgomery DC, Peck EA (1992) Introduction to linear regression analysis. Wiley, New YorkGoogle Scholar
  26. 26.
    Arora JS (1989) Introduction to optimum design. McGraw Hill, New YorkGoogle Scholar
  27. 27.
    Gill PE, Murray W (1981) Practical optimization. Academic, New YorkGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2008

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringEswari Engineering CollegeChennaiIndia
  2. 2.Department of Mechanical EngineeringCoimbatore Institute of TechnologyCoimbatoreIndia

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