2022
DOI: 10.1007/s00170-022-10337-6
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Correction of mould cavity geometry for warpage compensation

Abstract: Warpage is one of the most challenging defects occurring in plastic injection moulded parts. Various approaches to overcome this issue have been proposed in the literature, but they all provide only partial solutions to the problem. This paper proposes a new method for the compensation and minimisation of warpage. The method is based on Mould Cavity (MC) correction. In contrast to other similar methods, here the MC correction is accomplished through a direct comparison of the local deviations of the warped par… Show more

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Cited by 2 publications
(6 citation statements)
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“…The normal-vector method, developed by Kastelic et al [25], involves an iterative adjustment of the cavity shape. This adjustment is carried out by computing the normal vector at each surface node of the warped geometry mesh and identifying its intersection point with the corresponding desired geometry surface.…”
Section: Normal-vector Methodsmentioning
confidence: 99%
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“…The normal-vector method, developed by Kastelic et al [25], involves an iterative adjustment of the cavity shape. This adjustment is carried out by computing the normal vector at each surface node of the warped geometry mesh and identifying its intersection point with the corresponding desired geometry surface.…”
Section: Normal-vector Methodsmentioning
confidence: 99%
“…This method is inspired by experimental cavity shape compensation, where discrete measurements of produced parts inform adjustments [18,19,24]. However, this so-called reverse geometry method [25] requires identical meshes with corresponding nodes for both the deformed and ideal shapes. Method (3): Kastelic et al [25] introduced an alternative method for updating the cavity shape.…”
Section: Introductionmentioning
confidence: 99%
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“…In another iterative method, the objective function is the difference to the desired geometry and it is computed locally [11]. With this local objective function, the geometry can be adjusted locally to reduce each objective function with each iteration.…”
Section: Introductionmentioning
confidence: 99%