Modelling the Geometrical Accuracy for Different Part Geometries and Process Parameters when Broaching Fir-Tree Slots in Turbine Disks

Abstract Constructive measures in the design of aircraft engines aiming for CO2 and NOx emission reduction result in miniaturization of the components, e.g. the rotating turbine disks. The resulting filigree structures determine a reduction of the resistance against elastic workpiece deformations during the machining process. This leads to increasing demands on the cutting process to maintain the required form and position tolerances. In turbine disks, fir-tree slots as the fixing for the turbine blades are classified as safety-critical components. Currently, the profiled slots are manufactured by broaching. In order to guarantee the required component quality of the resulting fir-tree structure, it is necessary to examine the tool design systematically. By using FE simulations, it is possible to predict geometrical deviations after broaching and to perform counter measurements in tool design. In this paper, an innovative approach is presented, which combines an empirical-analytical cutting force model and numerical FE simulations to model the elastic deformations during the cutting process. Therefore, empirical cutting force information are used as input data for the dynamic FE simulations. The results are then analyzed regarding the achievable form and position tolerances when broaching profile grooves. This paper presents a parameter study on workpiece and process parameters and an evaluation of their impact regarding the geometrical accuracy in broaching.

[1]  Dragos Axinte,et al.  An experimental analysis of damped coupled vibrations in broaching , 2007 .

[2]  A. Klink,et al.  ECM roughing of profiled grooves in nickel-based alloys for turbomachinery applications , 2019, Procedia Manufacturing.

[3]  Thomas Bergs,et al.  Influence of an Additional Indexing Rotary Axis on Wire EDM Performance for the Automated Manufacture of Fir Tree Slots , 2019, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy.

[4]  Frederik Zanger,et al.  Simulation Approach for the Prediction of Surface Deviations Caused by Process-Machine-Interaction During Broaching , 2013 .

[5]  Fritz Klocke,et al.  A hybrid approach using machine learning to predict the cutting forces under consideration of the tool wear , 2019, Procedia CIRP.

[6]  Berend Denkena,et al.  Prediction of Temperature Induced Shape Deviations in dry Milling , 2015 .

[7]  Dragos Axinte,et al.  Broaching: Cutting tools and machine tools for manufacturing high quality features in components , 2020 .

[8]  J. Sölter,et al.  Development and Validation of a Hybrid Model for the Prediction of Shape Deviations in dry Machining Processes , 2015 .

[9]  Ekkard Brinksmeier,et al.  Prediction of shape deviations in machining , 2009 .

[10]  Volker Schulze,et al.  Component Distortion due to a Broaching Process , 2015 .

[11]  Fritz Klocke,et al.  Model-based analysis in finish broaching of inconel 718 , 2018, The International Journal of Advanced Manufacturing Technology.