Version 1
: Received: 10 October 2024 / Approved: 11 October 2024 / Online: 14 October 2024 (05:18:27 CEST)
How to cite:
Leng, Y.; Sanjon, C. W.; Tan, Q.; Groche, P.; Hauptmann, M.; Majschak, J.-P. Study of Parameters Influencing Wrinkles in Deep Drawing of Fiber-Based Materials Using Automatic Image Detection. Preprints2024, 2024100868. https://doi.org/10.20944/preprints202410.0868.v1
Leng, Y.; Sanjon, C. W.; Tan, Q.; Groche, P.; Hauptmann, M.; Majschak, J.-P. Study of Parameters Influencing Wrinkles in Deep Drawing of Fiber-Based Materials Using Automatic Image Detection. Preprints 2024, 2024100868. https://doi.org/10.20944/preprints202410.0868.v1
Leng, Y.; Sanjon, C. W.; Tan, Q.; Groche, P.; Hauptmann, M.; Majschak, J.-P. Study of Parameters Influencing Wrinkles in Deep Drawing of Fiber-Based Materials Using Automatic Image Detection. Preprints2024, 2024100868. https://doi.org/10.20944/preprints202410.0868.v1
APA Style
Leng, Y., Sanjon, C. W., Tan, Q., Groche, P., Hauptmann, M., & Majschak, J. P. (2024). Study of Parameters Influencing Wrinkles in Deep Drawing of Fiber-Based Materials Using Automatic Image Detection. Preprints. https://doi.org/10.20944/preprints202410.0868.v1
Chicago/Turabian Style
Leng, Y., Marek Hauptmann and Jens-Peter Majschak. 2024 "Study of Parameters Influencing Wrinkles in Deep Drawing of Fiber-Based Materials Using Automatic Image Detection" Preprints. https://doi.org/10.20944/preprints202410.0868.v1
Abstract
The evaluation of wrinkles in deep-drawn fiber-based materials is crucial for the assessment of product quality and the optimization of manufacturing processes. Wrinkles, a common phenomenon in deep-drawing paper materials with high drawing depths, significantly impair the appearance and mechanical properties of the final product. The objective of this study is to identify the key process parameters affecting wrinkling and to deepen the understanding of their roles and interactions using wrinkle data for deep-drawn paper products. Image analysis techniques are employed, supported by a specially constructed darkroom platform to ensure uniform light intensity for capturing photographs. An automated program is developed for the detection and evaluation of wrinkle characteristics and distribution, which allows the free choice of the region to be detected and the representation of the wrinkle geometry not limited by the number. To enhance the precision of this program, the ellipticity is initially rectified for products without flanges, specifically cup-shaped deep-drawn products. The ellipticity is caused by the pronounced springback effect of the paperboard. The approach is employed to investigate the impact of material properties, blank holder force, drawing depth, drawing clearance, and punch speed on wrinkling formation after the deep drawing process. The findings reveal that the blank holder force and drawing clearance are critical factors in wrinkle formation, with higher forces generally leading to increased wrinkle numbers.
Keywords
Wrinkle recognition; Deep drawing; Paperboard; Process Parameter; Image identification
Subject
Engineering, Mechanical Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
