Minimization of surface roughness in 5-axis milling of turbine blades

Abstract

The Reynolds number of turbine blades can be reduced by decreasing the surface roughness of the blades, which decreases energy loss in energy production systems. Due to the challenges of the polishing process in reducing roughness of machined blades, the application of optimized machining parameters to decrease surface roughness is a practical solution. Virtual machining system is explored in this research to improve the efficiency of machined parts. The aim of this research is to provide a virtual machining system that can predict and effectively reduce roughness in gas turbine blade 5-axis machining operations. The machining parameters were optimized using Genetic algorithm to reduce surface roughness. The turbine blades were machined using a 5-axis CNC machine tool, and the surface roughness of the machined parts was measured using a CMM machine to validate the developed methodology in the study. The optimized machining parameters result in a 26.2% reduction in observed surface roughness and a 27.3% reduction in expected surface roughness in the machined blades. The developed virtual machining system can be used to improve the surface quality of machined turbine blades and hence improve the efficiency of gas turbines during the power production in gas turbines.