TY - JOUR A1 - Jablonka, Kevin Maik A1 - Ai, Qianxiang A1 - Al-Feghali, Alexander A1 - Badhwar, Shruti A1 - Bocarsly, Joshua D. A1 - Bran, Andres M. A1 - Bringuier, Stefan A1 - Brinson, L. Catherine A1 - Choudhary, Kamal A1 - Circi, Defne A1 - Cox, Sam A1 - de Jong, Wibe A. A1 - Evans, Matthew L. A1 - Gastellu, Nicolas A1 - Genzling, Jerome A1 - Gil, María Victoria A1 - Gupta, Ankur K. A1 - Hong, Zhi A1 - Imran, Alishba A1 - Kruschwitz, Sabine A1 - Labarre, Anne A1 - Lála, Jakub A1 - Liu, Tao A1 - Ma, Steven A1 - Majumdar, Sauradeep A1 - Merz, Garrett W. A1 - Moitessier, Nicolas A1 - Moubarak, Elias A1 - Mouriño, Beatriz A1 - Pelkie, Brenden A1 - Pieler, Michael A1 - Ramos, Mayk Caldas A1 - Ranković, Bojana A1 - Rodriques, Samuel G. A1 - Sanders, Jacob N. A1 - Schwaller, Philippe A1 - Schwarting, Marcus A1 - Shi, Jiale A1 - Smit, Berend A1 - Smith, Ben E. A1 - Van Herck, Joren A1 - Völker, Christoph A1 - Ward, Logan A1 - Warren, Sean A1 - Weiser, Benjamin A1 - Zhang, Sylvester A1 - Zhang, Xiaoqi A1 - Zia, Ghezal Ahmad Jan A1 - Scourtas, Aristana A1 - Schmidt, K. J. A1 - Foster, Ian A1 - White, Andrew D. A1 - Blaiszik, Ben T1 - 14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon N2 - Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines. KW - Large Language model KW - Hackathon KW - Concrete KW - Prediction KW - Inverse Design KW - Orchestration PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-589961 DO - https://doi.org/10.1039/d3dd00113j VL - 2 IS - 5 SP - 1233 EP - 1250 PB - Royal Society of Chemistry (RSC) AN - OPUS4-58996 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Poka, Konstantin A1 - Merz, Benjamin A1 - Epperlein, Martin A1 - Hilgenberg, Kai T1 - Integration of the whole digital chain in a unique file for PBF-LB/M: practical implementation within a digital thread and its advantages N2 - 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. T2 - Additive Manufacturing for Products and Applications 2023 CY - Lucerne, Switzerland DA - 11.09.2023 KW - Laser Powder Bed Fusion KW - Digital Twin KW - Data Integrity KW - Process Chain Integration KW - Computer Aided Manufacturing PY - 2023 SN - 978-3-031-42982-8 DO - https://doi.org/10.1007/978-3-031-42983-5_7 SN - 2730-9576 VL - 3 SP - 91 EP - 114 PB - Springer CY - Cham AN - OPUS4-58363 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Merz, Benjamin A1 - Nilsson, R. A1 - Garske, C. A1 - Hilgenberg, Kai T1 - Camera-based high precision position detection for hybrid additive manufacturing with laser powder bed fusion N2 - Additive manufacturing (AM) in general and laser powder bed fusion (PBF-LB/M) in particular are becoming increasingly important in the field of production technologies. Especially the high achievable accuracies and the great freedom in design make PBF-LB/M interesting for the manufacturing and repair of gas turbine blades. Part repair involves building AM-geometries onto an existing component. To minimise the offset between component and AM-geometry, a precise knowledge of the position of the component in the PBF-LB/M machine is mandatory. However, components cannot be inserted into the PBF-LB/M machine with repeatable accuracy, so the actual position will differ for each part. For an offset-free build-up, the actual position of the component in the PBF-LB/M machine has to be determined. In this paper, a camera-based position detection system is developed considering PBF-LB/M constraints and system requirements. This includes finding an optimal camera position considering the spatial limitations of the PBF-LB/M machine and analysing the resulting process coordinate systems. In addition, a workflow is developed to align different coordinate systems and simultaneously correct the perspective distortion in the acquired camera images. Thus, position characteristics can be determined from images by image moments. For this purpose, different image segmentation algorithms are compared. The precision of the system developed is evaluated in tests with 2D objects. A precision of up to 30μm in translational direction and an angular precision of 0.021∘ is achieved. Finally, a 3D demonstrator was built using this proposed hybrid strategy. The offset between base component and AM-geometry is determined by 3D scanning and is 69μm. KW - Laser powder bed fusion KW - Additive manufacturing KW - Hybrid repair KW - Machine vision KW - Image processing KW - Position detection PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-568583 DO - https://doi.org/10.1007/s00170-022-10691-5 SP - 1 EP - 16 PB - Springer AN - OPUS4-56858 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Poka, Konstantin A1 - Ali, Sozol A1 - Saeed, Waleed A1 - Merz, Benjamin A1 - Epperlein, Martin A1 - Hilgenberg, Kai T1 - Design and implementation of a machine log for PBF-LB/M on basis of IoT communication architectures and an ETL pipeline N2 - AbstractPowder Bed Fusion with Laser Beam of Metals (PBF-LB/M) has gained more industrial relevance and already demonstrated applications at a small series scale. However, its widespread adoption in various use cases faces challenges due to the absence of interfaces to established Manufacturing Execution Systems (MES) that support customers in the predominantly data-driven quality assurance. Current state-of-the-art PBF-LB/M machines utilize communication architectures, such as OPC Unified Architecture (OPC UA), Message Queuing Telemetry Transport (MQTT) and Representational State Transfer Application Programming Interface (REST API). In the context of the Reference Architecture Model Industry 4.0 (RAMI 4.0) and the Internet of Things (IoT), the assets, particularly the physical PBF-LB/M machines, already have an integration layer implemented to communicate data such as process states or sensor values. Missing is an MES component acting as a communication and information layer. To address this gap, the proposed Extract Transform Load (ETL) pipeline aims to extract relevant data from the fabrication of each build cycle down to the level of scan vectors and additionally to register process signals. The suggested data schema for archiving each build cycle adheres to all terms defined by ISO/TC 261—Additive Manufacturing (AM). In relation to the measurement frequency, all data are reorganized into entities, such as the AM machine, build cycle, part, layer, and scan vector. These scan vectors are stored in a runtime-independent format, including all metadata, to be valid and traceable. The resulting machine log represents a comprehensive documentation of each build cycle, enabling data-driven quality assurance at process level. KW - FAIR data KW - Data-driven quality assurance KW - Laser powder bed fusion PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-601256 DO - https://doi.org/10.1007/s40964-024-00660-7 SN - 2363-9512 SP - 1 EP - 12 PB - Springer Science and Business Media LLC AN - OPUS4-60125 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Poka, Konstantin A1 - Ali, Sozol A1 - Saeed, Waleed A1 - Merz, Benjamin A1 - Epperlein, Martin A1 - Hilgenberg, Kai T1 - Quality assurance via a cyber physical system of a PBF-LB/M machine N2 - Powder Bed Fusion with Laser Beam of Metals (PBF-LB/M) faces challenges in reproducibility and quality assurance, even for widely applied alloys like AlSi10Mg. This work introduces a digital provenance framework for PBF-LB/M, showcased through the EOS M 300–4 multi-laser machine. An Extract, Transform, Load (ETL) pipeline autonomously captures machine data, including scan vectors as well as process signals, and organizes them into a Digital Shadow (DS). The DS is further extended by external data sources, such as Melt Pool Monitoring (MPM), to enable comprehensive analysis and root cause identification. This approach ensures continuous data representation and facilitates the development of new quality metrics. Moreover, the framework enhances quality assurance and traceability, supports compliance with industry standards, and improves productivity. It also enables more precise cost calculations and predictive maintenance. By addressing these challenges, the framework is essential for advancing PBF-LB/M in industrial applications, achieving greater consistency and scalability in production. KW - PBF-LB/M KW - Data driven quality assurance KW - Data engineering KW - Digital shadow PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-625187 DO - https://doi.org/10.1007/s40964-025-00978-w SN - 2363-9520 VL - 10 IS - 3 SP - 1771 EP - 1783 PB - Springer Science and Business Media LLC AN - OPUS4-62518 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Merz, Benjamin T1 - Precise Position Detection for Repair of Gas Turbine Blades using PBF-LB/M N2 - 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. T2 - International Symposium Additive Manufacturing 2023 (ISAM 2023) CY - Dresden, Germany DA - 30.11.2023 KW - additive manufacturing KW - powder bed fusion of metals utilizing a laser beam KW - PBF-LB/M KW - hybrid repair KW - position detection KW - high-resolution camera PY - 2023 AN - OPUS4-59193 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Merz, Benjamin A1 - Poka, Konstantin A1 - Mohr, Gunther A1 - Hilgenberg, Kai A1 - Polte, Julian T1 - Advanced camera calibration for lens distortion correction in hybrid manufacturing processes: An exemplary application in laser powder bed fusion (PBF-LB/M) N2 - Hybrid additive manufacturing is becoming increasingly important in the field of additive manufacturing. Hybrid approaches combine at least two different manufacturing processes. The focus of this work is the build-up of geometries onto conventionally manufactured parts using Powder Bed Fusion with Laser Beam of Metals (PBF-LB/M). The hybrid build-up requires a precise position detection system inside the PBF-LB/M machines to determine the exact position of the existing component. For this purpose, high-resolution camera systems can be utilized. However, the use of a camera system is associated with several challenges. The captured images are subject to various distortions of the optical path. Due to these distortions, it is not possible to use the images for measurements and, therefore, it is not possible to calculate the positions of objects. In this study a homography matrix is calculated to correct keystone distortion in the images. Different calibration patterns have been tested for the calculation of the homography matrix. The influence of the number of calibration points on the precision of position detection of objects is determined. Furthermore, the influence of an additional camera calibration by using ChArUco boards is evaluated. The result is a camera calibration workflow with associated calibration pattern for a precise position detection of parts inside PBF-LB/M machines allowing a hybrid build-up with minimum physical offset between base component and build-up. T2 - euspen’s 24th International Conference & Exhibition CY - Dublin, Ireland DA - 10.06.2024 KW - Additive manufacturing KW - Hybrid build-up KW - Position detection KW - Camera calibration PY - 2024 SP - 1 EP - 4 AN - OPUS4-60599 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Merz, Benjamin A1 - Schmidt, Jonathan A1 - Poka, Konstantin A1 - Mohr, Gunther A1 - Polte, Julian A1 - Hilgenberg, Kai T1 - Impact of illumination technique on the detectability of irregularities in high-resolution images of visual in-situ process monitoring in Laser Powder Bed Fusion N2 - The layerwise geometry build-up of additive manufacturing (AM) enables the possibility of in-situ process monitoring. The objective is the detection of irregularities during the build cycle, ensuring component quality and process stability. Focus of this work is the visual in-situ monitoring of the process of powder bed fusion with laser beam of metals (PBF-LB/M). Current state of the art visual monitoring systems for PBF-LB/M are limited by low resolution, allowing the detection of gross flaws. In this work a 65 Mpixel high-resolution monochrome camera is integrated into a commercial PBF-LB/M machine enabling a spatial resolution of approx. 17.2 µm/Pixel. The observed inhomogeneities are clustered into directly detectable irregularities, and indirectly detectable irregularities that can be inferred from the surface. In parallel, two different illumination techniques are realized in the process chamber and compared. The impact of the distinct illumination technique, direct light and dark field, on the identification of irregularities is evaluated. KW - Powder bed fusion with laser beam of metals KW - In-situ monitoring KW - High-resolution camera KW - Illumination technique PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-610929 DO - https://doi.org/10.1016/j.procir.2024.08.079 SN - 2212-8271 VL - 124 SP - 98 EP - 103 PB - Elsevier B.V. AN - OPUS4-61092 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Merz, Benjamin A1 - Knobloch, Tim A1 - Mohr, Gunther A1 - Hilgenberg, Kai T1 - Concepts for bridging voids in metal additive manufacturing for repair of gas turbine blades using laser powder bed fusion N2 - One of the main advantages of additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) is the possibility to manufacture complex near-net-shape components. Therefore, the PBF-LB/M process is becoming increasingly important for the manufacturing and repair of gas turbine blades. Despite the great freedom in design, there are also limitations to the process. Manufacturing overhangs or bridging voids are some of the main challenges. In the conventional PBF-LB/M process, overhangs with angles up to 45° can be manufactured. However, gas turbine blades feature voids for cooling, which have to be bridged when using PBF-LB/M. In this work, different concepts for bridging voids are developed for future application in gas turbine blade repair. For this purpose, a test geometry is derived from the tip area of a gas turbine blade as a reference. By changing the initial geometry of the reference body, different designs for bridging voids are developed based on the PBF-LB/M requirements. Subsequently, these distinct designs are manufactured by PBF-LB/M. The different approaches are compared with respect to their volume increase. In addition, the specimens are visually inspected for warpage, shrinkage and imperfections by overheating. Out of the seven concepts developed, three concepts can be recommended for gas turbine blade repair based on low volume increase, distortion and shrinkage. T2 - Metal Additive Manufacturing Conference - MAMC 2022 CY - Graz, Austria DA - 26.09.2022 KW - Repair of gas turbine blades KW - Laser Powder Bed Fusion (PBF-LB/M) KW - Selective Laser Melting (SLM) KW - Design for Additive Manufacturing (DfAM) KW - Bridging voids KW - Supportless PY - 2022 SP - 19 EP - 28 PB - TU Graz CY - Graz AN - OPUS4-55868 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Merz, Benjamin A1 - Poka, Konstantin A1 - Nilsson, R. A1 - Mohr, Gunther A1 - Hilgenberg, Kai T1 - On the challenges of hybrid repair of gas turbine blades using laser powder bed fusion N2 - 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. T2 - LiM 2023 CY - Munich, Germany DA - 26.06.2023 KW - Laser powder bed fusion KW - Additive manufacturing KW - Hybrid repair KW - Position detection KW - High-resolution camera PY - 2023 SP - 1 EP - 9 AN - OPUS4-57836 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Merz, Benjamin T1 - On the challenges of hybrid repair of gas turbine blades using laser powder bed fusion N2 - 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. T2 - LiM 2023 CY - Munich, Germany DA - 26.06.2023 KW - Laser powder bed fusion KW - Additive manufacturing KW - Hybrid repair KW - Position detection KW - High-resolution camera PY - 2023 AN - OPUS4-57837 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Benjamin, Merz T1 - Advanced camera calibration for lens distortion correction in hybrid additive manufacturing processes N2 - Hybrid additive manufacturing is becoming increasingly important in the field of additive manufacturing. Hybrid approaches combine at least two different manufacturing processes. The focus of this work is the build-up of geometries onto conventionally manufactured parts using laser-based powder bed fusion of metals (PBF-LB/M). The hybrid build-up requires a precise position detection system inside the PBF-LB/M machines to determine the exact position of the existing component. For this purpose, high-resolution camera systems can be utilized. However, the use of a camera system is associated with several challenges. The captured images are subject to various distortions of the optical path. Due to these distortions, it is not possible to use the images for measurements and, therefore, it is not possible to calculate the positions of objects. In this study a homography matrix is calculated to correct keystone distortion in the images. Different calibration patterns have been tested for the calculation of the homography matrix. The influence of the number of calibration points on the precision of position detection of objects is determined. Furthermore, the influence of an additional camera calibration by using ChArUco boards is evaluated. The result is a camera calibration workflow with associated calibration pattern for a precise position detection of parts inside PBF-LB/M machines allowing a hybrid build-up with minimum physical offset between base component and build-up. T2 - euspen’s 24th International Conference & Exhibition CY - Dublin, Ireland DA - 10.06.2024 KW - Aditive Manufacturing KW - Hybrid build-up KW - Position detection KW - Camera calibration PY - 2024 AN - OPUS4-60600 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -