2018
DOI: 10.4314/njt.v37i2.15
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Optimization of weld strength properties of tungsten inert gas mild steel welds using the response surface methodology

Abstract: The rise in the failure of mechanical components, some of which are attributable to poor weld joints has given rise to research study on the optimization of weld joint strengths. The quality of welds is highly dependent on the right combination of input process parameters. Irrespective of the welding process, the need for the right combination of input process parameters cannot be over emphasized. To achieve a desired weld quality, the weld features such bead geometry and the mechanical properties were examine… Show more

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Cited by 9 publications
(6 citation statements)
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“…The signal-to-noise ratio is measured by Adequate (Adeq) Precision. A signal-to-noise ratio higher than 4 is acceptable in most design analysis [21]. In this study, the signalto-noise ratio is 110.19, which signifies an adequate signal.…”
Section: Analysis Of Variance (Anova)mentioning
confidence: 70%
See 1 more Smart Citation
“…The signal-to-noise ratio is measured by Adequate (Adeq) Precision. A signal-to-noise ratio higher than 4 is acceptable in most design analysis [21]. In this study, the signalto-noise ratio is 110.19, which signifies an adequate signal.…”
Section: Analysis Of Variance (Anova)mentioning
confidence: 70%
“…The main determining factors in ANOVA are the Fvalue and p-value. Sada [21], described F-value as the variance of the group means, while p-value is the probability of getting a result at the extreme. Table 4 presents the ANOVA analysis for the quadratic model (thermal resistance).…”
Section: Analysis Of Variance (Anova)mentioning
confidence: 99%
“…a) & (b) repersent the normal probalility curve for toughness and hardness and this plot is used to check the adquancy of model. as all points are in a straight line,it can concluded that model is adequate[16][17][18].…”
mentioning
confidence: 89%
“…Hence the need for a study of their comparative performance. The response surface methodology (RSM) has been a widely used approach for modeling of welding processes (Sada, 2018). It encompasses a group of statistic based approaches which cuts across applications in model building, experimental designs, exploration of factor effects and searching for optimal conditions (Kalil et al, 2000).…”
Section: Sada Somentioning
confidence: 99%