2012
DOI: 10.1177/0954405412461328
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Flow forming optimization based on diametral growth using finite element method and response surface methodology

Abstract: Flow forming as a precise locally plastic deformation is applied to fabricate thin-walled seamless tubes. Diametral growth as a dimensional defect that occurrs in a flow-formed tube is studied numerically and experimentally in this article. Flow forming of an AISI 321 steel tube is investigated using a finite element method with a dynamic explicit approach. The efficient parameters on the diametral growth are determined using experimental outcomes. The parameters considered are the thickness reduction (%), the… Show more

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Cited by 18 publications
(7 citation statements)
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References 21 publications
(26 reference statements)
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“…Previous studies mainly focused on the processing parameters of traditional power spinning (Bhatt et al, 2017;Wang et al, 2020;Jalali et al, 2012). (Xiao et al, 2014) established the metal flow model during CRS and derived the calculation formula of equivalent strains of the spun parts on the basis of the upper bound method.…”
Section: Influence Of Process Parameters On the Forming Results Of Large-sized Cylindrical Parts During Counter-roller Spinning 1 Introdumentioning
confidence: 99%
“…Previous studies mainly focused on the processing parameters of traditional power spinning (Bhatt et al, 2017;Wang et al, 2020;Jalali et al, 2012). (Xiao et al, 2014) established the metal flow model during CRS and derived the calculation formula of equivalent strains of the spun parts on the basis of the upper bound method.…”
Section: Influence Of Process Parameters On the Forming Results Of Large-sized Cylindrical Parts During Counter-roller Spinning 1 Introdumentioning
confidence: 99%
“…[19] develop a characterization of the process through the use of a particular classic DoE design (Box-Behnken), which is strictly related with RSM (response surface methodology) evaluation of the results. [20] use fractional factorial DoE and graphical methods (RSM) in order to characterize the variables of their model for steel. The authors propose and optimize a set of variables, which are built by simulation trials of validation.…”
Section: Investigative Methodologiesmentioning
confidence: 99%
“…Results of ANOVA analysis confirm roller tip radius as most crucial parameter effective tube surface finish followed by thickness reduction ratio. Aghchai et al [48] [49] have used Taguchi method for optimization of inner rib thickness during simulation of the neck-in process of the AA6061-T6 alloy. They have used mandrel support span, mandrel speed, feed rate and roller diameter as input/control variable and adopted S/N ratio, response chart and average response chart method for optimization of the inner rib.…”
Section: Modelling Of the Process Using The Design Of Experiments (Domentioning
confidence: 99%