2014
DOI: 10.1016/j.proeng.2014.12.442
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Parameter Optimization for Surface Roughness and Wall Thickness on AA5052 Aluminium alloy by Incremental Forming using Response Surface Methodology

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Cited by 47 publications
(29 citation statements)
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“…The process parameters are considered significance to the experiment if there is a large angled slope of the straight line. We can see that all the points are relatively closed to the straight line and thus that the data follow a normal distribution [12]. ANOVA was used to determine the optimal input values which allow to minimize the forming force.…”
Section: Experimental Design Optimizationmentioning
confidence: 99%
“…The process parameters are considered significance to the experiment if there is a large angled slope of the straight line. We can see that all the points are relatively closed to the straight line and thus that the data follow a normal distribution [12]. ANOVA was used to determine the optimal input values which allow to minimize the forming force.…”
Section: Experimental Design Optimizationmentioning
confidence: 99%
“…Bagudanch et al [21] concluded that the spindle speed and s are the most critical parameters, and the interactions between f and s, t and d, and spindle speed with f also have a significant influence on the surface roughness. Mugendiran et al [22] studied incremental forming to optimize surface roughness by controlling the effects of forming parameters. e obtained results indicated that the primary parameters influencing the arithmetic mean surface roughness value (Ra) are f, spindle speed, and t, excluding the interactions among the three parameters.…”
Section: Introductionmentioning
confidence: 99%
“…Mugenderan et. al [16] had attempting to optimize the metal forming parameters such as surface roughness and sheet thickness after forming which is to obtain minimum surface roughness and maximum wall thickness in incremental forming. Cus and Zuperl [17] briefly present a compensation method in milling in order to take into account tool deflection during cutting condition optimization or tool path generation.…”
Section: Introductionmentioning
confidence: 99%