JOURNAL ARTICLE
CONTROL OF THE DEFORMATIONS GENERATED DURING THE MANUFACTURING PROCESS OF METAL SLITTER CIRCULAR KNIVES.
Published In: DYNA - Ingeniería e Industria, 2025, v. 100, n. 1. P. 1 1 of 3
Database: Art Source Ultimate 2 of 3
Authored By: Jimbert, Pello; Amezua, Xabier; Guraya, Teresa; Fernández, Roberto; Iturrondobeitia, Maider 3 of 3
Abstract
In this work, deformations produced during the manufacturing process of AISI D2 steel circular knives for metal slitters have been measured. For that, using a Coordinate Measuring Machine (CMM), measurements were performed at different points of both faces of 13 knives extracted from different stages of the manufacturing process, including a cryogenic treatment, to analyze its influence on the generated deformations. To analyze the deformations of each knife, the following characteristics were defined for each of its two faces: the flatness, the conicity and the peak-to-peak value and the number of undulations of several curves defined by measurements. The results obtained allowed to identify possible origins of the deformations and were analyzed to draw conclusions and try to propose improvements in the manufacturing process. Finally, as a test, a measurement was performed with a structured light 3D scanner and it was observed that with 3D scanners, measurements can be performed in much less time. However, further studies are needed to determine whether these 3D scanners are accurate enough to be used in this type of study. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:DYNA - Ingeniería e Industria. 2025/01, Vol. 100, Issue 1, p1
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2025
- ISSN:0012-7361
- DOI:10.52152/D11297
- Accession Number:183532067
- Copyright Statement:Copyright of DYNA - Ingeniería e Industria is the property of UK Zhende Publishing Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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