Prediction of thinning of the sheet metal in the program AutoForm and its experimental verification

Abstract

The manufacture of press-formed parts often involves deep-drawing operations. Deep drawing, however, can be deemed an industrial branch in its own right. Today, many experimental as well as numerical methods are available for designing and optimizing deep drawing operations. The best option, however, is to combine both approaches. The present paper describes one such investigation. Here, measurements and numerical simulation were used for mapping the impact of anisotropy on thickness variation in a spherical-shaped drawn part of DC01 steel. Variation in sheet thickness was measured on spherical-shaped drawn parts of various geometries by means of two cameras, and evaluated with digital image correlation using the ARAMIS software from the company GOM. The forming experiment was carried out on an INOVA 200 kN servohydraulic testing machine in which the force vs. piston displacement curve was recorded. The same experiment was then numerically simulated and analyzed using the AUTOFORM software. Various parameters were monitored, such as thinning, strain magnitude, formability, and others. For the purpose of this simulation, a series of mechanical tests was conducted to obtain descriptions of the experimental material of 1.5 mm thickness. A material model was constructed from the tests data involving the work-hardening curve, the impact of anisotropy, and the forming limit diagram. Specifically, these tests included tensile tests, the Nakajima test, and the stacked test, which were carried out to determine materials data for the model. The actual sheet thickness was measured on a sectioned spherical-shaped drawn part using a NIKON optical microscope. The variations in thickness along defined lines on the sectioned drawn part were compared with the numerical simulations data using digital image correlation. The above-described experimental programme is suitable for calibrating a material model for any computational software and can correctly solve deep-drawing problems.