Definition and validation of a customized classification system for sheet metal bending parts

Definition and validation of a customized classification system for sheet metal bending parts

Daniel Schmid, Marion Merklein

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Abstract. The industry demands an increasing individualization, which leads to a rising variety of sheet metal parts. The consequence for sheet metal manufacturers are larger amounts of product data, smaller batch sizes and a larger quantity of different parts per year. The challenge for an efficient company is the availability and use of the corporate product data. Classification is a suitable tool for organizing corporate product data sets. In order to better reflect the individualization of customer demands and the resulting flexible manufacturing processes in a classification system, a method is needed to adapt the classification system based on the frequently used feature list. In the context of this paper, features are defined and parts are classified that are manufactured with the technology of air bending. It is a contribution to the creation of more precise approaches to the sheet metal part classification with simultaneous validation by a measurable characteristic. Focus is placed on the validation of the system with empirical measurement data. This allows every company to optimize and validate their own classification system.

Optimization, Bending, Sheet Metal

Published online 3/17/2023, 6 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Daniel Schmid, Marion Merklein, Definition and validation of a customized classification system for sheet metal bending parts, Materials Research Proceedings, Vol. 25, pp 323-328, 2023


The article was published as article 40 of the book Sheet Metal 2023

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

[1] Bowen DT, Russo IM, Cleaver CJ et al. (2022) From art to part: Learning from the traditional smith in developing flexible sheet metal forming processes. Journal of Materials Processing Technology Volume 299(Article 117337):1–18.
[2] Kleiner M, Schilling R (1992) Umformtechnik. Ideen, Konzepte und Entwicklungen. Vieweg+Teubner Verlag, Wiesbaden.
[3] Trzepieciński T (2020) Recent Developments and Trends in Sheet Metal Forming. Metals – Open Access Metallurgy Journal 10, 779(6):1–53.
[4] Guldi A (2005) Unternehmensspezifisches Klassifikationssystem zur effizienten Datenverwaltung (mit Anwendungsszenarien aus der Praxis). Abschlußbericht des Verbundprojektes “Klassifikationssysteme automatisiert erstellen” (KLASTER). Univ.-Verl. Karlsruhe, Karlsruhe
[5] Liu Z-j, Li J-j, Wang Y-l et al. (2004) Automatically extracting sheet-metal features from solid model. J Zhejiang Univ Sci 5(11):1456–1465.
[6] Greska W, Franke V, Geiger M (1997) Classification problems in manufacturing of sheet metal parts. Computers in Industry 33:17–30.
[7] Duflou JR, Váncza J, Aerens R (2005) Computer aided process planning for sheet metal bending. A state of the art. Computers in Industry 56(7):747–771.
[8] Gupta RK, Gurumoorthy B (2013) Classification, representation, and automatic extraction of deformation features in sheet metal parts. Computer-Aided Design(45):1469–1484.
[9] Šugár P, Šugárová J, Kolník M (2011) Technology-Based Sheet Metal Classification and Coding System. Journal for Technology of Plasticity 36(1):1–8.
[10] Greska W (1995) Wissensbasierte Analyse und Klassifizierung von Blechteilen. Bericht aus dem Lehrstuhl für Fertigungstechnologie, LFT. Zugl.: Erlangen, Nürnberg, Univ., Diss., 1995. Fertigungstechnik – Erlangen, vol 49. Hanser, München
[11] Hagenah H (2003) Simulationsbasierte Bestimmung der zu erwartenden Maßhaltigkeit für das Blechbiegen. Zugl.: Erlangen-Nürnberg, Univ., Diss., 2002. Fertigungstechnik – Erlangen, vol 141. Meisenbach, Bamberg
[12] George ML, Maxey J, Price M et al. (2016) Das Lean Six Sigma Toolbook. Verlag Franz Vahlen GmbH.
[13] Söderberg R, Lindkvist L, Wärmefjord K et al. (2016) Virtual Geometry Assurance Process and Toolbox. Procedia CIRP 43:3–12.