Robust parametric optimization for investment casting process of a turbine vane

Abstract

Abstract Investment casting technology is an important manufacturing technology for the turbine guide vanes of the aero-engine, which directly affects the performance of the engine. However, most of the researches on the investment casting process of the vane is mainly based on the development of the materials, while the process parameters are less researched. The purpose of this paper is to perform a robust optimization for the process parameters of the investment casting of a typical vane. Firstly, a three-dimensional casting simulation model is established based on the ProCAST® software. Five key process parameters are chosen and their uncertainties are specified. A set of desired parameters are firstly obtained by conducting a deterministic optimization using a design of experiment (DOE) method. Next, a second-order response surface model (RSM) is built with Box-Behnken design based on the initial optimization results. Finally, an RSM-based robust parametric optimization with AMGA algorithm is proposed, deriving several Pareto solutions. By comparing and analyzing every solution, an optimal parameter scheme is developed by considering high quality of the casting and robustness of the casting process.