Aerospace industry requires the production of complex, multi-functional components with very low geometrical tolerances using difficult to machine materials such as Ti-6Al-4V. One of the main challenges when machining such materials is the resulting part distortion after milling due to the release of residual stresses generated in previous manufacturing steps such as forging or heat treatment. To prevent costly scrap parts and manual rework, finite element method (FEM) can be utilized to predict resulting part distortion during the machining process development phase. This paper presents a novel approach for part distortion simulation by directly integrating relevant machining data from computer aided manufacturing (CAM) system for the FEM using Boolean subtraction operations. A developed software interface enables a step-by-step mechanical material removal simulation providing manufacturers with an efficient and flexible tool for automated process evaluation. The approach is implemented in a laboratory setup using commercial CAM and FEM systems and evaluated by using aerospace relevant demonstration parts.
REFERENCES(18)
1.
BOWDEN D., HALLEY J., 2001, Aluminium Reliability Improvement Program, final report 60606, Boeing Co. Chic.
BILKHU R., 2020, Machining Strategies for Distortion Control During High Speed Machining, doctoral thesis, Department of Advanced Manufacturing Research Centre, The University of Sheffield.
PENG H., HOU Z., CHEN X., LI T., LUO J., LI X., 2021, Effect of Temperature and Cyclic Loading on Stress Relaxation Behavior of Ti–6Al–4V Titanium Alloy, Mater. Sci. Eng., A, 824, 141789, https://doi.org/10.1016/j.msea....
GLAVICIC M., FURRER D., SHEN G., 2010, A Rolls-Royce Corporation Industrial Perspective of Titanium Process Modelling and Optimization: Current Capabilities and Future Needs, J. Strain Anal. Eng. Des., 45, 329–336. https://doi.org/10.1243/030932....
MOEHRING H.-C., MAUCHER C., BECKER D., STEHLE T., EISSELER R., 2023, The Additive-Subtractive Process Chain - a Review, J. Mach. Eng., https://doi.org/10.36897/jme/1....
WEI Y., WANG X.W., 2006, Computer Simulation and Experimental Study of Machining Deflection Due to Original Residual Stress of Aerospace Thin-Walled Parts, Int. J. Adv. Manuf. Technol., 33/3–4, 260–265, https://doi.org/10.1007/s00170....
CERUTTI X., 2015, Numerical Modelling and Mechanical Analysis of the Machining of Large Aeronautical Parts, Machining Quality Improvement. ParisTech, Ecole doctorale no364, Sciences Fondamentales et Appliquees.
LANDWEHR M., SCHMID S., HOLLA V., GANSER P., BERGS T., RUESS M., SCHRÖDER K.-U., 2021, The Finite Cell Method for the Prediction of Machining Distortion Caused by Initial Residual Stresses in Milling, Procedia CIRP, 102, 144–149, https://doi.org/10.1016/j.proc....
FAN L., TIAN H., LI L., YANG Y., ZHOU N., HE N., 2020, Machining Distortion Minimization of Monolithic Aircraft Parts Based on the Energy Principle, Metals, 10/12, https://doi.org/10.3390/met101....
KUMAR K., PAULRAJ G., 2014, Analysis and Optimization of Fixture Under Dynamic Machining Condition with Chip Removal Effect, J. Intell. Manuf., 25, https://doi.org/10.1007/s10845....
CERUTTI X., MOCELLIN K., HASSINI S., BLAYSAT B., DUC E., 2017, Methodology for Aluminium Part Machining Quality Improvement Considering Mechanical Properties and Process Conditions, CIRP J. Manuf. Sci. Technol., 18, 18–38, https://doi.org/10.1016/j.cirp....
MAIER S., HABENICHT T., HOFFMANN M., YU H., MAUTHNER G., TENG C., FORTNA J., BLEICHER F., 2025, Methodology for Element Selection and Clustering in Multi-Axis Directed Energy Deposition Simulation, Procedia CIRP, 133, 644–649, https://doi.org/10.1016/j.proc....
GEISERT C., UHLMANN E., POLTE J., 2025, Intelligent Manufacturing - a New Understanding of Systems Integration, J. Mach. Eng., 25/2, 5–12, https://doi.org/10.36897/jme/2....
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.