Multivariate modelling of variability in sheet metal forming

de Souza, T. and Rolfe, B. 2008, Multivariate modelling of variability in sheet metal forming, Journal of materials processing technology, vol. 203, no. 1-3, pp. 1-12.

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Title Multivariate modelling of variability in sheet metal forming
Author(s) de Souza, T.
Rolfe, B.
Journal name Journal of materials processing technology
Volume number 203
Issue number 1-3
Start page 1
End page 12
Total pages 12
Publisher Elsevier SA
Place of publication Aedermannsdorf, Switzerland
Publication date 2008-07-18
ISSN 0924-0136
1873-4774
Keyword(s) springback
sheet metal forming
robustness
variation
probabilistic modelling
Summary The inherent variability in incoming material and process conditions in sheet metal forming makes quality control and the maintenance of consistency extremely difficult. A single FEM simulation is successful at predicting the formability for a given system, however lacks the ability to capture the variability in an actual production process due to the numerical deterministic nature. This paper investigates a probabilistic analytical model where the variation of five input parameters and their relationship to the sensitivity of springback in a stamping process is examined. A range of sheet tensions are investigated, simulating different operating windows in an attempt to highlight robust regions where the distribution of springback is small. A series of FEM simulations were also performed, to compare with the findings from the analytical model using AutoForm Sigma v4.04 and to validate the analytical model assumptions.

Results show that an increase in sheet tension not only decreases springback, but more importantly reduces the sensitivity of the process to variation. A relative sensitivity analysis has been performed where the most influential parameters and the changes in sensitivity at various sheet tensions have been investigated. Variation in the material parameters, yield stress and n-value were the most influential causes of springback variation, when compared to process input parameters such as friction, which had a small effect. The probabilistic model presented allows manufacturers to develop a more comprehensive assessment of the success of their forming processes by capturing the effects of inherent variation.
Language eng
Field of Research 091099 Manufacturing Engineering not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2008
Copyright notice ©2007, Elsevier B.V.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30017196

Document type: Journal Article
Collection: Centre for Material and Fibre Innovation
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