Search Results

Springback prediction for stamped components is a challenging task for Automotive Industry. Automotive Manufacturers are working to reduce the springback effect of sheet metal stampings caused due to elastic behavior of materials with the help of changes to manufacturing process and part geometry. Recent development in Finite Element Analysis (FEA) studies made it possible for the industry to rely on stamping simulation. There is always a gap between the springback predicted from stamping simulation and the actual stamped part. Currently FEA techniques are trying to close this gap. The objective of this study is to minimize this gap using DFSS method for predicting the springback and optimizing the simulation parameters with the help of LS-Dyna FEM tool. The behavior of material with different simulation parameters has been studied in this paper and the ones that best correlate with actual data are identified.

Springback is a major phenomenon in sheet metal forming process that has to be tackled to achieve the desired product with greater dimensional accuracy. Springback occurs due to elastic recovery of sheet metal after the stamping process. The automobile industry is gradually moving from use of conventional steels to advanced high strength steels (AHSS) for their light weight and greater strength properties; however AHSS possesses greater springback effect due to higher elastic limit which proves to be difficult to deal with the springback effect. Hence it is imperative that the counter measures are taken to minimize the springback effect. The purpose of the study is to showcase various factors that influence the prediction of springback phenomenon. In this study the simulation results are compared with scanned data of actual stamped panels and their deviation is studied.

Automotive industry's migration to usage of HSS (High Strength Steels), AHSS (Advance High Strength Steels) from conventional steels for their low weight and high strength properties has had its significant effects on die wear. The unpredictability of die wear can pose manufacturing issues, for example, undesirable tool life. Hence die wear has been gaining immense attention and lot of research work has been carried out to provide a die wear prediction method. This paper focuses on the method of estimating wear mathematically based on the mechanics behind die wear phenomenon. This is also an effort to study wear on die for an automotive component in critical areas for which the amount of wear are calculated. This study is further to be correlated with production data from die maintenance record, explicit measurement of die wear, etc., to validate the estimation.