Global versus cluster-wise regression analyses for prediction of bead geometry in MIG welding process

Abstract In this paper, an attempt is made to establish input–output relationships in MIG welding process through regression analyses carried out both globally (i.e., one set of response equations for the entire range of the variables) as well as cluster-wise. It is important to mention that the second approach makes use of the entropy-based fuzzy clusters. The investigation is based on the data collected through full-factorial design of experiments. Results of the above two approaches are compared and some concluding remarks are made. The cluster-wise regression analysis is found to perform a slightly better than the global approach in predicting weld bead-geometric parameters.

[1]  Ill-Soo Kim,et al.  Sensitivity analysis for process parameters influencing weld quality in robotic GMA welding process , 2003 .

[2]  Ill-Soo Kim,et al.  A study on relationship between process variables and bead penetration for robotic CO2 arc welding , 2003 .

[3]  Y. S. Tarng,et al.  The Use of Fuzzy Logic in the Taguchi Method for the Optimisation of the Submerged Arc Welding Process , 2000 .

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

[5]  D. Rosenthal Mathematical Theory of Heat Distribution during Welding and Cutting , 1941 .

[6]  Y. S. Tarng,et al.  Optimisation of the weld bead geometry in gas tungsten arc welding by the Taguchi method , 1998 .

[7]  N. Murugan,et al.  Prediction and optimization of weld bead volume for the submerged arc process. Part 2 , 2000 .

[8]  J I Lee,et al.  Prediction of process parameters for gas metal arc welding by multiple regression analysis , 2000 .

[9]  Manoranjan Dash,et al.  Entropy-based fuzzy clustering and fuzzy modeling , 2000, Fuzzy Sets Syst..

[10]  Chia-Ming Chang,et al.  The use of grey-based Taguchi methods to determine submerged arc welding process parameters in hardfacing , 2002 .

[11]  H. P. Seow,et al.  Effect of increasing deposition rate on the bead geometry of submerged arc welds , 1997 .

[12]  N. Murugan,et al.  Effect of submerged arc process variables on dilution and bead geometry in single wire surfacing , 1993 .

[13]  N. Murugan,et al.  Prediction and comparison of the area of the heat-affected zone for the bead-on-plate and bead-on-joint in submerged arc welding of pipes , 1999 .

[14]  Min Jou,et al.  Experimental Study and Modeling of GTA Welding Process , 2003 .

[15]  M. J. Bibby,et al.  An analysis of curvilinear regression equations for modeling the submerged-arc welding process , 1993 .

[16]  N. Murugan,et al.  Prediction and optimization of weld bead volume for the submerged arc process - Part 1 , 2000 .

[17]  Jiju Antony,et al.  Application of design of experiments to a spot welding process , 2003 .

[18]  N. Murugan,et al.  Effects of MIG process parameters on the geometry of the bead in the automatic surfacing of stainless steel , 1994 .