Laser assisted forming of sheet metals

Friction aided deep drawing of sheet metals using polyurethane ring and auxiliary metal punch. Part 1: experimental observations on the deep drawing of aluminium thin sheets and foils

A new deep drawing process of sheet metals is developed to facilitate small-lot production of deep cups with large drawing ratio. In this process, unlike the conventional deep drawing method, a few drawn cups are always stacked on the punch and used as a part of punch for the subsequent deep drawing of a given blank. Before drawing a new blank, a drawn cup which is in contact with the punch is stripped off. The repetition of such stripping and drawing operations makes it possible to carry out both the first-stage drawing and the subsequent slight redrawings in one drawing operation using only one pair of punch and die. In this paper, this new deep drawing process is applied to the production of tapered cups and the main feature of the process is shown.

<div class="htmlview paragraph">In this paper the deep drawing of sheet metal forming method, is very useful in industrial field because of its efficiency. In order to obtain the optimal products in deep drawing process, the deep drawing is affected by many process variables, such as blank shapes, profile radii of punch and die, formability of materials and so on. Especially, blank shape is very important formability factor. In this study, in order to investigate the effects of blank shape, we suggested three kinds of blank shapes and examined the friction test about three conditions. We measured the punch load distribution according to punch stroke under the conditions of profile radii of punch and die and observed the punch load of non-axisymmetric formability.</div>

Radial Lorentz force augmented deep drawing for large drawing ratio using a novel dual-coil electromagnetic forming system

6 - Deep drawing of sheet metals using the friction-actuated blank-holding technique

Deep drawing of sheet metals using the friction-actuated blank-holding technique

In order to improve adaptability to evolving manufacturing processes in an era marked by mass customization and individualization, while also meeting geopolitical climate objectives, it is necessary to employ more sustainable methods in sheet metal forming to enhance flexibility. Metal based rigid tooling systems require a lot of material and energy resources, when aiming for high flexibility and scalability with respect to small batch size production. To reduce the overall resource consumption and to meet climate restrictions, non-metallic tooling approaches can counteract these issues when aiming for individualization in sheet metal forming. Compared to conventional metal-based tooling approaches, wood-based forming tools may enable a potential resource reduction (e.g., carbon footprint) and offer an alternative tooling approach for sheet metal forming. Although the mechanical performance of wood is lower compared to conventional tooling steel, certain wood-based forming tools can potentially be implemented for sheet metal forming. In this work a feasibility study of wood-based tooling materials is executed to investigate the mechanical performance on drawn sheet metal parts in a deep drawing operation. Different composite structures are investigated for wooden forming tools of black locust (robinia pseudoacacia).

Abstract. A promising approach to meet ecological and economical challenges in production industry is the combination of additive manufacturing and forming, which enables the production of hybrid parts. The fusion of the two technologies has the potential to use the benefits of both process classes. One example for the combination of additive manufacturing and forming is a process chain consisting of laser-based directed energy deposition (DED-LB/M) to apply a wear resistant coating on a sheet metal and a subsequent deep drawing process to achieve the final geometry of the component. However, the presence of the local reinforcement influences the subsequent sheet metal forming process. In order to gain more knowledge about the process chain a numerical approach is performed. In this work, the influence of a coating using Bainidur® AM applied by DED-LB/M on the formability of the case hardening steel 16MnCr5 in a deep drawing process is evaluated. For this purpose, a numerical model is built and validated by comparison with experimental results. The finite-element-model serves as the basis for the investigation on the influence of the location of the additively applied coating on the deep drawing process and also enables a deeper understanding of the process.

In metallurgical processes, as for example cold rolling or deep drawing of sheet metal, it is frequently observed that the crystallographic texture, and with it the anisotropic mechanical properties of a material, evolve dynamically. Hence, to describe such processes, it is necessary to model the functional dependence of anisotropic material parameters on the texture, which itself can vary locally with the different plastic strain histories. In this work, we present a new data-oriented approach to parametrize the anisotropic yield function Barlat Yld2004-18p from micromechanical simulations for different textures. This is accomplished by applying supervised machine learning (ML) methods to express the relationship between different crystallographic textures and the material parameters of the yield function. The crystallographic textures are chosen to vary continuously between a random texture on the one hand side, and a unimodal Goss or Copper texture the other. These crystallographic textures are rather common in sheet metal forming. In this way, furthermore, the transition from isotropic plasticity to a rather severe case of anisotropy can be modeled, which is thought to mimic the dynamical evolution of the texture in a metallurgical process. It is found that a regularization strategy is necessary to circumvent the known non-uniqueness between Yld2004-18p parameters and the resulting plastic yield behavior. After this regularization, a unique relationship between the material parameters and the yield onset is established, making it possible to train different ML models with excellent accuracy and generalization properties to anisotropic plastic material behavior. The trained ML models are able to reliably predict the coefficients of unknown textures even with a small amount of training data and, thus, to correctly represent the yield behavior resulting from the various textures. The proposed method represents an efficient extension of the description of anisotropic plastic yielding as it establishes a data-oriented way to explicitly consider microstructural parameters in the material description, which opens new pathways to formulate material models that include the process history.

深絞りにおけるしわの抑制

Springback caused by elastic recovery is known to be a major disadvantage in sheet metal forming. Many studies focused on the prediction and compensation of springback in the bending process have used simulation and numerical methods, with experimental tests rarely being reported. A new approach, aimed at decreasing springback, is presented in this paper to solve the springback problem and provide a reference for other researchers. A new edge bending method called “incremental bending” has been developed and implemented on aluminum sheet at room temperature. Using this method, bending strain was lowered, leading to a reduction in springback. 3D Digital Image Correlation, an optical measurement technique, was adopted simultaneously to provide a high accuracy measurement of the full field strain distribution and springback curvature, making it very suitable for springback measurement. The experimental results show an obvious reduction of springback, which agrees well with the theoretical analysis. This work could help to minimize springback in sheet metal bending dramatically and improve formability and productivity, as well as provide a reference for researchers studying cold-bending. Details of the basic bending theory, experimental method, experimental results, and analysis will be demonstrated in the following content.

Integrating bending function into multi-axis machine tools will broaden the capability of current manufacturing equipment. However, capability study must be conducted in order to warranty further exploration of such a hybrid manufacturing strategy. This paper presents the capability study of a heat-assisted Mill-Bend process that implements sheet metal bending on a 3-axis milling machine setup. Specifically, the hypothesis is that sheet metal bending can be effectively performed on milling machines, yielding a commensurable accuracy and repeatability as those from traditional bending machines. To this end, two quality characteristics are evaluated—bending angle and bending radius. In the first part of the work, Taguchi parameter design was used to obtain the optimal process parameters. Under the optimal process parameters, the heat-assisted Mill-Bend process is able to produce an improved consistency on bending angle compared to traditional bending process (15.16% and 17.13% reductions of standard deviation in inner angle and outer angle, respectively) although experiencing a slight increase in spring back. In the second part, an elastic–plastic deformation model was used to predict bending radius. The result shows that the predicted radius agrees well with experimental data. In conclusion, heat-assisted Mill-Bend process produces commensurable bending performance when the process is optimized.

Series production of sheet metal components in press shops is permanently subjected to an increasing pressure in time, cost and quality. Varying sheet metal properties due to batch fluctuations and changing process conditions lead to an increase of try out time phase and scrap rate, resulting in a demand for adaptive control strategies for deep drawing. Today, these chal-lenges are met by integrating sensors and actuators into tool structure which measure and control part quality, mainly through blank draw-in. However, such tool-based control systems require a complex and cost-intensive modification of the existing die or press technology. Against this background, the active adjustment of blank position prior the deep drawing process realized with an intelligent transfer and positioning system as a promising approach towards economic and technical aspects. This paper deals with blank positioning and its sensitivity to quality-related failures of deep drawn sheet metal components like splits and wrinkles. Therefore, a numerical study was conducted on a deep drawing process of an exemplary structural part geometry, wherein a typical fluctuation of material parameters and variation of local friction conditions was simulated. Subsequently, correlations between process disturbance and blank draw-in were elaborated, thus using local draw-in values as controlled variables for a closed loop system. Sim-ulation results showed that the manipulating parameter, i.e. the blank position prior deep draw-ing, reveals a significant influence on the draw-in and therefore on the component s quality. An essential finding of this study is the numerical proof of concept for this new deep drawing control strategy, demonstrated for different process conditions. Finally, disturbances in the deep drawing process considered could be successfully controlled by adapting the blank position.

Cross-profile deep drawing of magnesium alloy AZ31 sheet metal for springback analysis under various temperatures

In the first paper, it has been shown that in 304 austenitic stainless steels, the martensitic phase induced by cold working, generates a flow stress growth according to deforming conditions given to the material. Moreover, constitutive equations for the aggregate have been formulated under a uniaxial stress state. In this second paper, the study has been extended to develop an incremental formulation to analyze multiaxial plastic deformation problems. The incremental constitutive model is formulated by considering the austenite-martensite phase transformation, flow stress under a multiaxial stress state, compliance of each phase and temperature, whose effects are included simultaneously in each parameter. A method of rigid-plastic finite-element analysis is proposed in order to estimate the distributions of transformed martensite and flow stress growth of materials subjected to general kinds of cold working such as forging, extrusion, and deep drawing. The temperature rise distributions due to plastic deformation have been co-analyzed using the above formulation. Some compression tests accompanied by temperature changes have been carried out and they were compared with the theoretical results. Good agreement was confirmed between them. It is demonstrated that the proposed method can be used successfully to determine distributions of both strain-induced martensitic phase and flow stress in austenitic stainless steels under cold-working conditions.