Numerical investigation of the effect of process parameters to optimize a superplastic forming process

Abstract

Superplastic forming (SPF) is an alternative manufacturing method to produce complex shapes in one step without assembling operations which are not possible with other methods. SPF process enables to get near net shape products without surface finish operation necessities. SPF process can produce parts with nearly 1000% elongations with good mechanical properties. SPF process also reduces the weights of the products because it eliminates assembly processes. Furthermore, SPF process increases cycles of components before failure. Mentioned assets of SPF make it a very important process choice in aviation industry, in which good mechanical properties, low weights and long service lives are required.The main purpose of this thesis is to investigate process parameters of SPF process for Ti6Al4V material using finite element method (FEM) in order to obtain an optimum process which results in both good product quality and reasonable cost. For this purpose, first analysis results were compared to an experimental study to test accuracy of the used method, next the process parameters were investigated for rectangular and conical parts. Then, a tool was developed to be used in the factory for estimating process time of SPF process with given process parameters. Finally, application of SPF process is conducted for an aircraft blowout door in order to choose an optimum process for production.Keywords: Superplastic Forming, Superplasticity, Finite Element Method, Machine Learning, Data Mining, Aviation, Aerospace