Analysis of aluminum alloys deep drawing process via finite element method

Usage of 6xxx and 7xxx series aluminum alloys in industry becomes widespread day by day by means of high specific strength and weight acquisition performance. In this study, AA6082-T6 aluminum alloy sheet metal was used. A large number of products in plenty of sectors are obtained via plastic forming of aluminum alloy sheets. However, determination of process efficiency is quite hard since plastic forming has non linear characteristics and process depends on plenty of variables consisting of material, environment and process parameters. On the other hand, it is important to manufacture true part as soon as possible with minimal defect on the first try in competitive environment of modern-days. Trial and error method in manufacturing leads to cost increase due to waste product, workmanship and manufacturing lead time increase. Correspondingly, usage of finite element softwares becomes widespread each passing day. Real manufacturing process has to be modeled efficiently and consistency comparison has to be performed to validate the results obtained from finite element simulations. In this study, variation of limiting drawing ratio (LDR) which is the measure of formability in deep drawing process was investigated via physical experiments and finite element analyses depending on blankholder pressure, drawing speed and lubrication conditions. Aluminum sheets were prepared for deep drawing process in various increasing radii to obtain maximum value of LDR and deep drawn between cylindrical deep drawing molds (punch, die and blankholder) with a velocity and pressure adjustable hydraulic press. Consistency comparison was performed between the results obtained from physical experiments and finite element analyses performed depending on blankholder pressure, drawing speed and lubrication conditions. Effects of varying punch speed and drawing pressure depending on stroke as well as lubrication conditions on formability were investigated via finite element analyses due to the costly and time-consuming nature of physically modeling of the process.