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Additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) are rapidly gaining popularity in repair applications. Gas turbine components benefit from the hybrid repair process as only damaged areas are removed using conventional machining and rebuilt using an AM process. However, hybrid repair is associated with several challenges such as component fixation and precise geometry detection. This article introduces a novel fixturing system, including a sealing concept to prevent powder sag during the repair process. Furthermore, a high-resolution camera within an industrial PBF-LB/M machine is installed and used for object detection and laser recognition. Herein, process related inaccuracies such as PBF-LB/M laser drift is considered by detection of reference objects. This development is demonstrated by the repair of a representative gas turbine blade. The final offset between AM build-up and component is analysed. An approximate accuracy of 160 μm is achieved with the current setup.
Additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) are rapidly gaining popularity in repair applications. Gas turbine components benefit from the hybrid repair process as only damaged areas are removed using conventional machining and rebuilt using an AM process. However, hybrid repair is associated with several challenges such as component fixation and precise geometry detection. This article introduces a novel fixturing system, including a sealing concept to prevent powder sag during the repair process. Furthermore, a high-resolution camera within an industrial PBF-LB/M machine is installed and used for object detection and laser recognition. Herein, process related inaccuracies such as PBF-LB/M laser drift is considered by detection of reference objects. This development is demonstrated by the repair of a representative gas turbine blade. The final offset between AM build-up and component is analysed. An approximate accuracy of 160 μm is achieved with the current setup.
The industrialization of AM is only possible by creating synergy with the tools of Industry 4.0. The system technology of Powder Bed Fusion with Laser beam of Metals (PBF-LB/M) reached a level of high performance in terms of process stability and material spectrum in the past years. However, the digital process chain, starting from CAD via CAM and plant-specific compila-tion of the manufacturing file exhibits media disruptions. The consequence is a loss of metadata. A uniform data scheme of simulation for Design for Additive Manufacturing (DfAM), the PBF-LB/M process itself and quality assurance is currently not realized within industry. There is no entity in the common data flows of the process chains, that enables the integration of these functionalities. As part of the creation of a digital quality infrastructure in the QI-Digital pro-ject, an integration of the CAD/CAM chain is being established. The outcome is a file in an advanced commercially available format which includes all simula-tions and manufacturing instructions. The information depth of this file extends to the level of the scan vectors and allows the automatic optimization and holis-tic documentation. In addition, the KPI for the economic analysis are generated by compressing information into a unique file combined with the application of a digital twin. The implementation and advantages of this solution are demon-strated in a case study on a multi-laser PBF-LB/M system. A build job contain-ing a challenging geometry is thermally simulated, optimized, and manufac-tured. To verify its suitability for an Additive Manufacturing Service Platform (AMSP), the identical production file is transferred to a PBF-LB/M system of another manufacturer. Finally, the achieved quality level of the build job is evaluated via 3D scanning. This evaluation is carried out in the identical entity of the production file to highlight the versatility of this format and to integrate quality assurance data.
Additive manufacturing (AM) technologies are becoming increasingly important, not only for the manufacture of parts, but also as repair technology that complement existing production technologies. Powder bed fusion of metals by laser beam (PBF-LB/M) combines the freedom in design with high achievable accuracy, making it ideal as a repair approach. However, there are still challenges in adapting process for repair applications. When mounting parts inside PBF-LB/M machines, their real position within the build volume is unknown. One goal of a repair process is to minimize the offset between the base component and the additively manufactured structure to reduce additional rework. For a minimum offset between component and additively manufactured structure, the actual position of the component has to be identified with high precision within the machine coordinate system (MCS). In this work a process setup is presented that allows the actual position of a gas turbine blade to be detected inside a PBF-LB/M machine. A high resolution camera with 65 megapixel is used for this purpose. The presented setup is implemented on a SLM 280 HL PBF-LB/M machine. In addition to the setup, a novel repair workflow using PBF-LB/M is presented. The developed setup and workflow consider inaccuracies in the component and camera mounting, as well as process inaccuracies. This includes keystone distortion correction by homography. The machine setup and workflow are used to repair a real gas turbine blade. Subsequently the offset between the turbine blade and the additivley manufactured structure is validated by 3D scanning the repaired part. The maximum offset is 160 µm. The presented approach can be extended to other geometries and PBF-LB/M machine manufacturers. The high-resolution camera approach is platform independent, which facilates the market penetration of PBF-LB/M repair processes.