Design of deep drawing die is a skilled and experienced based activity. Selection of die components is a vital step in the design process of a deep drawing die. This paper describes a knowledge based system (KBS) developed for the selection of major components of a deep drawing die. The proposed system uses production rule based approach of artificial intelligence (AI) and consists of eight mod...

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...

Servo press technology is gaining attention because its punch motion curve offers greater formability than that of a conventional stamping press. This study investigated the effect curves on circular cup extrusion–drawing process. Various were analyzed, and optimal for application was determined. Both process spring back U-shaped sheet metal investigated. In process, (Case A) three servo (Cases...

Although deep drawing process in the macro scale are well developed, the known concepts cannot be applied to micro deep drawing through directly scale down the specimen and tooling size due to the so-called size effects. Therefore, tensile test and micro deep drawing experiments were conducted to generate the knowledge for the micro deep drawing process. Stainless steel 304 foils with 4 differe...

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...

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 ...

Deep drawing is a sheet metal forming process which is widely used in manufacturing parts for automobile and air craft industries. In this paper, the mechanism of deformation, effect of the geometrical parameters involved and the defects encountered in the process are presented and discussed. These include: the radial clearance percentage, punch and die profile radii. Despite the number of publ...

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...

This study investigates the thickness variation behavior of deep drawing conical products under effect different forming parameters such as die wall inclination angle, punch velocity, sheet thickness, and metal type. Two types were used, low carbon (AISI 1008) galvanized steel sheets, 110 mm diameters circular blanks at 0.9 1.2mm formed by tooling set (punch, die, blank holder). The dies angles...

Sheet metal forming problems are typical in nature since they involve geometry, boundary and material non-linearity. Cup drawings involves many parameters like punch and die radius, clearance, lubrication, blank holding force and its trajectories etc. So designing the tools for cup drawing involves a lot of trial and error procedure. To reduce number of costly trial error steps, the process can...