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Content | same trend for T.V. This graph shows T.V is maximum (64.2 mm3) when F is at its maximum value with S at its minimum limit. T.V is minimum (42.5 mm3) when F is at its lower value with S at its upper limit. Conclusions The following conclusions were drawn from the above investigation: 1) The five-level factorial technique can be employed easily for developing mathematical models for predicting weld bead geometry within the workable re- gion of process parameters for SAW of pipes. 2) The models developed can be em- ployed easily in the form of a program for automatic and robotic welding for ob- taining the desired high-quality welds. 3) The welding process variable wire feed rate has a positive effect, but weld- ing speed has a negative effect on all the bead parameters. 4) Penetration reduces as welding voltage increases, but bead width and di- lution increase considerably with the in- crease in voltage. 5) Reinforcement is least when all the process variables are at their upper limit (+2) and F is at its lower limit. 6) Nozzle-to-plate distance has a neg- ative effect on all the bead parameters ex- cept bead width and total volume of the weld bead. 7) Most of the direct and interaction effects of the process variables on the bead parameters show generally con- vincing trends between cause and effect. References 1. Houldcroft, P. T. 1989. Submerged Arc Welding. Abington Publishers, U.K. 2. Annon. 1978. Principles of Industrial Welding.The James F. Lincoln Arc Welding Foundation, Cleveland, Ohio. 3. Balckman, S. 1981. Welded fabrication of subsea pipelines in the north sea. Welding and Metal Fabrication. 4. Murugan, N., Paramar, R. S., and Sud, S. K. 1993. Effect of submerged arc process vari- ables on dilution and bead geometry in single wire surfacing. Journal of Materials Processing Technology37: 767–780. 5. Adler, Y. P., Markov, E. V., and Gra- novsky, Y. V. 1975. The Design of Experiments to Find Optimal Conditions. MIR Publishers, Moskow. 6. Fisher, R. A. 1952. Statistical Methods for Research Workers, 12th edition. Edin- burgh, Oliver and Boyd. 7. Gupta, V. K., and Parmar, R. S. 1986. Fractional factorial techniques to predict di- mensions of the weld bead in automatic sub- merged arc welding. Journal of Inst. of Engi- neers(India) 70:67–71. 8. Arya, S. K., and Parmar, R. S. 1986. Mathematical models for predicting angular distortion in CO2— shielded flux cored arc welding. Proceedings of the International Conference on Joining of Metals, pp. 240–245. 9. Murugan, N., and Parmar, R. S. 1994. Ef- fects of MIG process parameters on the sur- facing of stainless steel. Journal of Materials Processing Technology41: 381–398. 10. Cochran, W. G., and Cox, G. M. 1963. Experimental Designs.Asia Publishing House, India. 11. Khuri, A. I., and Cornell, J. A. 1996. Re- sponse Surfaces, Design and Analysis.Marcol Dikker Inc., New York, N.Y. 12. Box, G. E. P., and Voule, P. V. 1955. The exploration and exploitation of response sur- faces. Biometrics11:287–322. 13. Montgomery, D. C., and Peck, E. A. 1992. Introduction to Linear Regression Analysis.John Wiley, New York, N.Y. 14. Davis, O. L. 1978. The Design and Analysis of Industrial Experiments.Longman, New York, N.Y. 15. SYSTAT Version 5.02. 1991. Systat, Inc. 16. Jackson, C. E, and Shrubsall, A. E. 1953. Control of penetration and melting ratio with welding technique. Welding Journal: 32(4): 172-s to 178-s. 294-s| OCTOBER 2000 RESEARCH/DEVELOPMENT/RESEARCH/DEVELOPMENT/RESEARCH/DEVELOPMENT/RESEARCH/DEVELOPMENT |
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