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AUTHOR(S): S. Praveen, S. Praveen Kumar
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TITLE Optimization and Prediction of Dilution Percentage in Submerged Arc Welding Process |
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ABSTRACT Weld dilution is an important feature of weld bead geometry that determines the mechanical and chemical properties of a welded joint. For submerged arc welding, several welding process parameters are reported to be controlling the dilution. This paper presents the effect of welding parameters like welding speed, welding current and voltage on penetration over mild steel plates. Three levels and three factors full factorial design method was used for conducting the experimental runs and linear regression models were developed accordingly. Nine experimental runs (L9) based on an orthogonal array Taguchi method were performed. The adequacy of the models was tested by applying S/N ratio and the predicted values from the models were plotted against the observed values through scatter diagram. Results showed that the proposed two level full factorial empirical models could predict the weld dilution with reasonable accuracy and ensure uniform weld quality. By using the Grey Relational Analysis technique, optimization of the complicated multiple process responses can be converted into optimization of a single grey relational grade and Optimization of a factor is the level with the highest grey relational grade. |
KEYWORDS Taguchi method; Dilution; Grey relational analysis; S/N ratio |
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Cite this paper S. Praveen, S. Praveen Kumar. (2021) Optimization and Prediction of Dilution Percentage in Submerged Arc Welding Process. International Journal of Mechanical Engineering, 6, 13-17 |
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