The design of multi stage deep drawing processes requires the evaluation of many process parameters such as the intermediate die geometry, the blank shape, the sheet thickness, the blank holder force, friction, lubrication etc..These process parameters have to be determined for the optimum forming conditions before the process design. In general sheet metal forming may involve stretching drawin...

in this paper, the deep drawing process of tailor welded blanks is simulated using the finite element modelling and verified using the experimental results available in the literature. then the effect of die and material properties on the welding line movement is investigated. it is seen that the most effective material parameters on weld line movement are different between sheet metal thicknes...

a new method for increasing ldr in deep drawing is application of anti-lock braking system (abs) on blank holder. in this method, instead of applying a constant force on blank and control the metal flow, the abs system holds and releases the blank several times (20 to 50 times) which results increasing ldr. this study investigates the effect of different parameters of abs on improving the condi...

In general, deep drawing products have various cross-section shapes such as cylindrical, rectangular and nonaxisymmetric shapes. The application of the surface area calculation to non-axisymmetric deep drawing process has not been published yet. In this research, a surface area calculation for non-axisymmetric deep drawing products with elliptical shape was constructed for a design of blank sha...

In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the...

In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent ...

The deep drawing is a process for shaping flat sheets into cup-shaped articles without failure or excessive localized thinning. The design and control of a deep drawing process depends not only on the material, but also on the condition of the tool material interface, the mechanics of plastic deformation, the equipment used, and the control of metal flow. The equipment and tooling parameters th...

This paper presents a thorough literature review of the size effects of friction in microforming. During miniaturization, the size effects of friction occur clearly. The paper first introduces experimental research progress on size effects of friction in both micro bulk and sheet forming. The effects of several parameters are discussed. Based on the experimental results, several approaches have...

Deep drawing is characterized by extremely complex deformation that influenced process characteristics such as die and punch shapes, blank shape, holding force, material properties, lubrication. The optimization of the deep a challenging issue due to complicated functions define relate parameters. However, essential enhance productivity product cost in process. In this paper, MATLAB toolbox (Pa...