Towards Efficient Modelling Of Macro And Micro Tool Deformations In Sheet Metal Forming

During forming, the deep drawing press and tools undergo large loads, and even though they are extremely sturdy\ud structures, deformations occur. This causes changes in the geometry of the tool surface and the gap width between the tools.\ud The deep drawing process can be very sensitive to these deformations. Tool and press deformations can be split into two\ud categories. The deflection of the press bed-plate or slide and global deformation in the deep drawing tools are referred to as\ud macro press deformation. Micro-deformation occurs directly at the surfaces of the forming tools and is one or two orders\ud lower in magnitude.\ud The goal is to include tool deformation in a FE forming simulation. This is not principally problematic, however, the FE\ud meshes become very large, causing an extremely large increase in numerical effort. In this paper, various methods are\ud discussed to include tool elasticity phenomena with acceptable cost. For macro deformation, modal methods or ’deformable\ud rigid bodies’ provide interesting possibilities. Static condensation is also a well known method to reduce the number of DOFs,\ud however the increasing bandwidth of the stiffness matrix limits this method severely, and decreased calculation times are not\ud expected. At the moment, modeling Micro-deformation remains unfeasible. Theoretically, it can be taken into account, but\ud the results may not be reliable due to the limited size of the tool meshes and due to approximations in the contact algorithms

Compensation of deep drawing tools for springback and tool-deformation

Manual tool reworking is one of the most time-consuming stages in the\ud preparation of a deep drawing process. Finite Elements (FE) analyses are now widely\ud applied to test the feasibility of the forming process, and with the increasing accuracy of the\ud results, even the springback of a blank can be predicted. In this paper, the results of an FE\ud analysis are used to carry out tool compensation for both springback and tool/press\ud deformations. Especially when high-strength steels are used, or when large body panels are\ud produced, tool compensation in the digital domain helps to reduce work and save time in the\ud press workshop. A successful compensation depends on accurate and efficient FE-prediction,\ud as well as a flexible and process-oriented compensation algorithm. This paper is divided in\ud two sections. The first section deals with efficient modeling of tool/press deformations, but\ud does not discuss compensation. The second section is focused on springback, but here the\ud focus is on the compensation algorithm instead of the springback phenomenon itself

A mixed elastoplastic / rigid plastic material model

A new integration algorithm for plastic deformation is derived in combination with the\ud anisotropic Hill’49 yield criterion. The algorithm degenerates to the Euler forward elastoplastic material\ud model for small deformations and to the rigid plastic material model for large strain increments. The new\ud model benefits from the advantages of both the elastoplastic and rigid plastic material models: accuracy and\ud fast convergence over a large range of strain increments. The performance of the new algorithm is tested by a\ud deep drawing simulation of a rectangular product. It can be concluded that the new algorithm performs well:\ud the plastic thickness strain distribution of the mixed model inclines towards the elastoplastic material mode

Numerical product design: Springback prediction, compensation and optimization

Numerical simulations are being deployed widely for product design. However, the accuracy of the numerical tools is not yet always sufficiently accurate and reliable. This article focuses on the current state and recent developments in different stages of product design: springback prediction, springback compensation and optimization by finite element (FE) analysis. To improve the springback prediction by FE analysis, guidelines regarding the mesh discretization are provided and a new through-thickness integration scheme for shell elements is launched. In the next stage of virtual product design the product is compensated for springback. Currently, deformations due to springback are manually compensated in the industry. Here, a procedure to automatically compensate the tool geometry, including the CAD description, is presented and it is successfully applied to an industrial automotive part. The last stage in virtual product design comprises optimization. This article presents an optimization scheme which is capable of designing optimal and robust metal forming processes efficiently

Advanced sheet metal forming

Weight reduction of vehicles can be achieved by using high strength steels or aluminum. The formability of aluminum can be improved by applying the forming process at elevated temperatures. A thermo-mechanically coupled material model and shell element is developed to accurately simulate the forming process at elevated temperatures. The use of high strength steels enlarges the risk of wrinkling. Wrinkling indicators are developed which are used to drive a local mesh refinement procedure to be able to properly capture wrinkling. Besides, to intensify the use of implicit finite element codes for solving large-scale problems, a method is developed which decreases the computational time of implicit codes by factors. The method is based on introducing inertia effects into the implicit finite element code. It is concluded that the computation time is decreased by a factor 5-10 for large-scale problems

Improvement of implicit finite element code performance in deep drawing simulations by dynamics contributions

To intensify the use of implicit finite element codes for solving large scale problems, the computation time of these codes has to be decreased drastically. A method is developed which decreases the computational time of implicit codes by factors. The method is based on introducing inertia effects into the implicit finite element code in combination with the use of iterative solvers. Another advantage of introducing inertia effects into an implicit finite element code is that it stabilizes the computation, especially when the problem is under-constrained. The dynamics contributions are successfully implemented for both the plane strain element (only displacement d.o.f.) and the Mindlin shell element (displacement and rotational d.o.f.). Deep drawing simulations are performed to investigate the performance of the dynamics contributions in combination with iterative solvers. It is concluded that the computation time can be decreased by a factor 5–10