Prediction of variation in dimensional tolerance due to sheet metal hydroforming using finite element analysis
Hydroforming of aluminum sheets is very important in the aircraft industry, due to the advantages of less wrinkling and cost effectiveness. Numerous research has been conducted in this field, which deals with the development of methods and tools to control accuracy of the bend and prediction of the springback after the sheet metal has been formed. Rivets are the most commonly used fasteners to fit together the subassemblies of the aircraft. The holes for riveting are punched after any forming operation due to the tensile and compressive deformations along the thickness of the sheet metal, which can affect the dimension and position accuracy of the hole. This incurs more cost and time due to the development of special dies for accurately punched holes. It is necessary to develop a method for predicting variation in the holes, which will increase the cost effectiveness of the process. In this research, sheet metal with pre-drilled holes was evaluated for a bending operation using a hydroforming technique. Sheet metal with a variety of thicknesses, bending radii, and bending angles was evaluated. Variation in the dimensional tolerance was attained using the minimum radial separation method. A dataset of dimensional variation in the holes was developed and used for development of the artificial neural network, which was able to predict the dimensional variation of the hole if an unknown pattern of inputs was provided. This study presents the prediction of the dimensional variation of holes due to sheet metal bending using the hydroforming technique.
Thesis (M.S.)--Wichita State University, Dept. of Mechanical Engineering.
Includes bibliographic references (leaves 74-78)