Schneidkanten werden in der industriellen Praxis oftmals gezielt gebrochen oder verrundet, um so die Kantenstabilität der Werkzeuge zu optimieren. Dabei ist jedoch zu beachten, dass eine zu groß ausgeführte Schneidkantenverrundung zu einer höheren Verfestigung der schergeschnittenen Blechbauteilkante führt und damit die Entstehung von Kantenrissen in nachfolgenden Umformprozessen begünstigt. Im Beitrag wird eine neuartige numerische Methode für die Vorauslegung von Schneidkantenradien vorgestellt. To increase the lifetime of shear cutting tools, cutting edges are often manually rounded in industrial practice. However, with cutting edge roundings being too big, the edge crack sensitivity of shear-cut sheet metal component edges is increasing. This paper presents a new numerical approach for an optimized selection of cutting edge radii. Stress peaks in the cutting tool and the edge crack sensitivity of sheet metal components are considered as optimization variables.
The ongoing digitization of production processes provides new possibilities and potentials for process monitoring of forming and stamping processes. The component quality achievable by these processes is strongly dependent on the properties of the sheet metal material, so that a permanent digital recording of material data offers high potential for monitoring each component produced. In this context, presented paper deals with a novel AI-based method for the direct determination of ma-terial parameters from measured punching force curves. Using software systems Python and Tensor-Flow, an artificial neural network was first set up to determine mechanical material parameters (out-put data) from punching force curves (input data). As data basis for the adopted neural network, force curves were measured during punching of various sheet metal materials using a punching tool equipped with a direct force measurement device. Punching force curves were experimentally deter-mined for the sheet metal materials DP1200, DP1000, DP800, DP600, HX380LA, DC03 and DX54. Additionally, tensile tests were performed for these sheet metal materials to determine ultimate tensile strengths (Rm), yield strengths (Rp0.2, Re), uniform strains (Ag), elongations at break (At) and strain hardening exponents (n). The presented paper reveals that neural networks can accurately quantify the relationship between characteristic parameters of punching force curves and the mentioned me-chanical material properties.
In order to experimentally identify process limits during punching with slant angle, a test tool was manufactured at the Institute for Metal Forming Technology (IFU) for in-situ measuring the horizontal punch deflection. The modular design of a test tool enabled the variation of numerous cutting parameters such as the “cutting clearance”, the “punch length” or the “slant angle”. Considering current lightweight construction trends in automotive industry, sheet metal materials HC340LA, DP600 and DP1000 were investigated, since these high-strength steel materials allow the use of relatively thin sheets in modern car body designs. As a result of investigations carried out in single stroke testings, a cutting parameter-dependent overview of maximum possible slant angles could be obtained, which was not yet available according to the current state of the art. Based on gained results, design guidelines for tools for punching with slant angles were derived, which were subsequently validated by endurance tests performed under lab conditions. In summary, the research work carried out does not only show a list of the maximum possible slant angles. Rather, it was possible to work out the insight that the process limits for punching with slant angle are assumed to be too conservative in industrial practice. For example even the high-strength sheet material DP1000 was punched reliably with a punch diameter of d=5mm up to a slant angle of 17.5°. In industrial practice, a cost-intensive cam solution would have been used from a slant angle of approx. 5°.
For economic or process-related reasons, punching of structural sheet metal components often has to be used for car bodies. The difference in angle of attack between punch and sheet metal component is referred to as “slant angle”. However, at the current state of the art, no precise information is available on the characteristics of cutting surfaces in relation to the slant angles. For this reason, cost-intensive slider units are used for comparatively small slant angles of around 10° in order to ensure series suitability of corresponding punching processes. In this respect, recent studies performed by the authors have shown that good cutting surface qualities can also be achieved for slant angles distinctly beyond 10°. This contribution presents an empirical test series for the characterization of cutting surface parameters when punching with a slant angle. Here, the experimental cutting surface analysis showed an asymmetric characteristic of the cutting surface along the hole circumference. Furthermore, the investigated sheet metal materials HC340LA, DP600 and DP800 revealed recurring tendencies regarding the parameters “edge draw-in”, “clean cut”, “fracture surface” and “burr height”, which had been combined to corresponding three-dimensional regression models. With these regression models, cutting simulations could be calibrated, allowing a quality prognosis of cutting surfaces achievable when punching at specific slant angles.
Die beim Lochen von Bauteilen aus Blech mit Blechlagewinkel erzielbaren Schnittflächenkenngrößen können nach aktuellem Stand der Technik nicht ausreichend präzise prognostiziert werden. Daher werden in der Praxis maximal realisierbare Blechlagewinkel meist zu konservativ abgeschätzt. Mit den in diesem Beitrag vorgestellten Schnittflächen-Regressionsmodellen kann der benötigte Einsatz von kosten- und wartungsintensiven Keilschiebern genauer bewertet und somit eine flexiblere, kostenoptimierte Gestaltung von Schneidwerkzeugen ermöglicht werden. Today, cutting surfaces achievable by punching sheet metal components with a slant angle cannot be predicted sufficiently precise. In industrial practicet, maximum slant angles applicable for shear cutting are therefore usually estimated rather conservatively. According to the regression model-based determination of cutting surfaces presented in this paper, demand for cost and maintenance-intensive cams can be evaluated more accurately, thus enabling a more flexible, cost-optimized design of cutting tools.
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