Optimization of weld bead geometry for stainless steel claddings deposited by FCAW

Abstract The quality of cladded components depends on the weld bead geometry, coefficients of shape of welds and dilution, which have to be controlled. Optimum range of bead parameters and dilution are required for better economy and to ensure the desired mechanical and corrosion resistant properties of the overlay. The above objectives can easily be achieved by developing mathematical equations to predict the weld bead geometry. This paper presents the development of such equations using the data obtained by conducting three factor five level factorial experiments. The experiments were conducted by depositing Type AISI 317L flux cored stainless steel wire onto IS: 2062 structural steel base plate. The results of the confirmation experiments showed that the models developed are able to predict the bead geometries and dilution with reasonable accuracy. The studies have indicated that both main and interaction effects of the process variables play a major role in determining the bead dimensions and dilution, and the effect of interaction between the process variables cannot be neglected. The process parameters were also optimized using response surface methodology (RSM) which will help the plant engineers to select and control the process variables effectively, to achieve the desired clad qualities.

[1]  M. Deaton,et al.  Response Surfaces: Designs and Analyses , 1989 .

[2]  D. W. Lyons,et al.  Experimental Approach to Selection of Pulsing Parameters in Pulsed GMAW A method for selection of process parameters in pulsed GMAW helps to efficiently develop welding procedures , 1999 .

[3]  S. Ramasamy,et al.  Design-of-Experiments Study to Examine the Effect of Polarity on Stud Welding An investigation of the factors that influence the quality of short duration drawn arc stud welding of steels , 2002 .

[4]  N. Murugan,et al.  Stainless steel cladding deposited by automatic gas metal arc welding , 1997 .

[5]  N. Murugan,et al.  Development of mathematical models for prediction of weld bead geometry in cladding by flux cored arc welding , 2006 .

[6]  Douglas C. Montgomery,et al.  Applied Statistics and Probability for Engineers, Third edition , 1994 .

[7]  R. H. Myers,et al.  Probability and Statistics for Engineers and Scientists , 1978 .

[8]  A. Sili,et al.  Single-pass laser beam welding of clad steel plate , 2004 .

[9]  William G. Cochran,et al.  Experimental Designs, 2nd Edition , 1950 .

[10]  Theodore T. Allen,et al.  Statistical process design for robotic GMA welding of sheet metal , 2002 .

[11]  M. J. Kang,et al.  Spatter Rate Estimation in the Short-Circuit Transfer Region of GMAW , 2003 .

[12]  Daoid Crosby Practical statistics for engineers and scientists , 1987 .

[13]  Y. S. Tarng,et al.  Process parameter selection for optimizing the weld pool geometry in the tungsten inert gas welding of stainless steel , 2002 .

[14]  Young-Soo Yang,et al.  Sensitivity analysis for process parameters in GMA welding processes using a factorial design method , 2003 .