Isar Aerospace adopts nebumind software for automated powder bed analysis
Isar Aerospace, Ottobrunn, based Bavaria, Germany, has reported it recently integrated software from nebumind GmbH, Taufkirchen, Germany, into its Laser Beam Powder Bed Fusion (PBF-LB) Additive Manufacturing process. The move is an attempt to automate the identification and reporting of defects during the application of a new powder layer, saving time and costs in manufacturing.
In the past, engineers had to evaluate the powder bed images in a manual process to find possible anomalies and assess their impact on component quality. The nebumind software is able to detect these defects through automated analysis of the powder bed images, providing the engineer with information for evaluating the quality of the manufacturing process.
As an emerging company in the space industry sector, Isar Aerospace relies on cutting-edge manufacturing techniques, such as PBF-LB, to manufacture complex engine components. One of the critical steps in Additive Manufacturing is the powder recoating conducted after each additively manufactured layer, as it is prone to error; if the surface to be exposed is not coated evenly and completely, this can lead to defects in the component.
Manual analysis of recoater images is time-consuming, error-prone and retrospectively
Nowadays, sensors and cameras integrated in the PBF-LB Additive Manufacturing machine to monitor the coating step. These are manually analysed for uncoated areas, damage to the recoater or other defects by engineers responsible for the process.
This approach is extremely time-consuming: for instance, if an additively manufactured metal component generates 2,500 recoater images and an engineer takes 3 seconds to analyse each image, they spend over 2 hours on this task for one build job alone. Moreover, as the analysis is conducted in a post-processing step, defects are usually only identified after a component has been manufactured.
To prevent this manual process, Isar Aerospace connected the nebumind software into its machine environment, automating the defect detection for each recoating layer. The software receives powder bed images before and after recoating, generated by an optical camera with a resolution of 1280 x 1024 pixels, and extracts them automatically via the direct machine interface. The software uses an algorithm to spot defects in the images automatically. For its algorithm, nebumind has employed primarily stable algorithms from image and edge detection. In addition, the positions of the defects are analysed across multiple layers to minimise the false positive rate.
By adopting the nebumind software, Isar Aerospace has reportedly realised a time saving of up to 80% compared to the previous manual analysis, as engineers can focus on the images labelled by the algorithm.
In-situ process analysis is designed to accelerate process development and eliminate the manufacturing of defective components
In the near future, nebumind’s defect recognition will reportedly be moved upstream from post-processing to in-process, so that the software will be able to point out possible anomalies immediately after coating, thereby enabling the user to stop the manufacturing process in the event of an irreparable defect.
To further automate the process, plans are in place to correlate the found recoater defects with other process data from the build job and CT data from the final quality check to identify root causes and prevent recoater defects from happening. In the long term, nebumind not only wants to monitor the manufacturing process with its software, but also intervene in the process in a regulating manner (eg, to stop the manufacturing process in the event of irreparable errors or to compensate for an incorrect coating in the subsequent layer).
