Automatic re-contouring of repair-welded tool moulds

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Denkena, B.; Dittrich, M.-A.; Heide, K.M.: Automatic re-contouring of repair-welded tool moulds. In: Procedia Manufacturing 40 (2019), S. 45-50. DOI: https://doi.org/10.1016/j.promfg.2020.02.009

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/16005

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Sum total of downloads: 14




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The process of repairing damaged tool moulds is conducted manually in the industry. This results in long process times as well as a high dependence of the repair result on the experience of the worker. After a visual inspection, the detected damages are removed by metal cutting and the missing material is filled by a build-up welding process. Afterwards, the target geometry is restored via machining re-contouring process. Because of the individual tool mould surface and welded seam, each repair case requires an individual machining strategy as well as toolpaths and process control parameters to ensure high surface quality and shape accuracy. This paper introduces an innovative design for re-contouring of repair-welded tool moulds, which takes into consideration the individual mould surface, repair welding and material properties. For that purpose, the actual geometry of the tool mould is measured directly in the CNC machine using an optical profile line sensor. Based on the measurement, the re-contouring process is planned automatically by means of a computer aided manufacturing (CAM) software. A material removal simulation with cutting force prognosis is carried out to adapt the process parameters individually with regard to repair time and surface quality. To set up the force and surface simulation model with high model quality, re-contouring experiments are carried out on welded seams made of 1.2343 (AISI H11) as well as on Toolox 44 and 1.2343 workpieces for comparison.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Maschinenbau

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1 image of flag of United States United States 6 42.86%
2 image of flag of Germany Germany 4 28.57%
3 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 7.14%
4 image of flag of France France 1 7.14%
5 image of flag of Czech Republic Czech Republic 1 7.14%
6 image of flag of China China 1 7.14%

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