Among Metallic Additive Manufacturing processes, Directed Energy Deposition (DED) processes are very promising for the Industry but still need to improve their reliability. Thermal behavior is a critical aspect for which uncontrolled phenomena can lead to part failure. Some thermal monitoring and closed-loop control methods have been developed to observe and regulate the heating of the processed part. However, these methods rely on local measures, thus provide partial information of thermal fields in the whole part volume. This paper proposes a method that combines diverse data to compute online a process indicator that is meaningful for the thermal state of the whole part, and hence for the control of the manufacturing of multi-beads multi-layer parts. A simulation-based model using thermal partial data is proposed. An online monitoring experiment is proposed for validation of the model. Relevance of the control method to ensure mechanical properties of the part is then tested.
REFERENCES(16)
1.
DING D., PAN Z., CUIURI D., LI H., 2015, Wire-Feed Additive Manufacturing of Metal Components: Technologies, Developments and Future Interests, Int. J. Adv. Manuf. Technol., 81, 465–481.
BANDYOPADHYAY A., TRAXEL K. D., 2018, Invited Review Article: Metal-Additive Manufacturing—Modelling Strategies for Application-Optimized Designs, Additive manufacturing, 22, 758–774.
DENLINGER E.R., HEIGEL J.C., MICHALERIS P., PALMER T.A., 2015, Effect of Inter-Layer Dwell Time on Distortion and Residual Stress in Additive Manufacturing of Titanium and Nickel Alloys, Journal of Materials Processing Technology, 215, 123–131.
GENG H., LI, J., XIONG J., LIN X., 2017, Optimisation of Interpass Temperature and Heat Input for Wire and Arc Additive Manufacturing 5A06 Aluminium Alloy, Science and Technology of Welding and Joining, 22, 472–483.
WU B., PAN Z., DING D., CUIURI D., LI H., FEI Z., 2018, The Effects of Forced Interpass Cooling on the Material Properties of Wire Arc Additively Manufactured Ti6Al4V alloy, Journal of Materials Processing Technology, 258, 97–105.
DING J., et al., 2011, Thermo-Mechanical Analysis of Wire and Arc Additive Layer Manufacturing Process on Large Multi-Layer Parts, Computational Materials Science, 50, 3315–3322.
ZHOU X., ZHANG H., WANG G., BAI X., 2017, Three-Dimensional Numerical Simulation of Arc and Metal Transport in Arc Welding Based Additive Manufacturing, Int. J. of Heat and Mass Transfer, 103, 521–537.
HU D., KOVACEVIC R., 2003, Sensing, Modeling and Control for laser-Based Additive Manufacturing, International Journal of Machine Tools and Manufacture, 43, 51–60.
FARSHIDIANFAR M.H., KHAJEPOUR A., GERLICH A., 2016, Real-Time Control of Microstructure in Laser Additive Manufacturing, International Journal of Advanced Manufacturing Technology, 82/5–8, 1173–1186.
CHEN Z., GUO X., SHI J., 2020, Hardness Prediction and Verification Based on Key Temperature Features During the Directed Energy Deposition Process, International Journal of Precision Engineering and Manufacturing - Green Technology, 8, 453–469.
CHABOT A., RAUCH M., HASCOËT J. Y., 2019, Towards a Multi-Sensor Monitoring Methodology for AM Metallic Processes, Welding in the World, 63/3, 759–769.
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.