Abstract
Modern aircraft engines require appropriate care and understanding of design and manufacturing. This is even more important, as the production of aerospace engines remains a manual process in many cases with limited data sources. Quality control has to consider verification of manufacturing and assembly steps through specific checks and controls whilst implementing additional data sources.
In this article, a review of the challenges with regard to controls, automation and process, and technical understanding for aerospace engine production and repair is provided. As this requires the collaboration of many teams and partners, an improvement and step change towards deeper understanding and process efficiency is required. As many operations remain manual, innovations in the way humans interact with technology and collaborate with industrial environments are needed.
This article demonstrates the creation and usage of the proposed solutions for collaboration, troubleshooting and error correction in jet engine assembly.
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Andulkar, M.: Development of Multimodal Collaborative Robot System using Hybrid Programming Methods. In: Shaker Verlag, Aachen (2018).
Bade, C., Hoffmeyer, A.: Industrielle Anwendung von Augmented Reality in der Fertigungsplanung bei der Volkswagen AG (2008).
Baitinger, M.: Virtual Factory – 3-D-Visualisierung in der Projektabwicklung von Lackieranlagen. In 11. IFF-Wissenschaftstage: Virtual Reality und Augmented Reality zum Planen, Testen und Betreiben technischer Systeme VR und AR – Automotive, Magdeburg pp.53-60 (2008).
Berger, U., Bilous, V., Noack, R., Andulkar, M.: Anwendung von der Augmented Reality für die Mensch-Roboter Interaktion bei der Fehlerbeseitigung und bei der Maschinenbedienung. In: INNTERACT 2016 3DSENSATION, Chemnitz (2016).
Buschbacher, J.: Augmented Reality in der Ausbildung – Elektroniker für Geräte und Systeme (2012), https://buschbacher.wordpress.com/2012/12/12/augmented-reality-in-der-ausbildung-elektroniker-fur-gerate-und-systeme/ last accessed 2020/03/23.
Chen, X., Fang, H., Lin, T.-Y., Vedantam, R., Gupta, S., Dollar, P., Zitnick, C.: Microsoft COCO Captions: Data Collection and Evaluation Server. arXiv:1504.00325 (2015).
Dmitriev, S., Burlakov, V., Popov, O., Popov, D.: Technological Processes and Quality Control in Aircraft Engine Maintenance. In: Aviation, vol. 19, no. 3, pp. 133–137 (2015).
Handa, A., Patraucean, V., Badrinarayanan, V., Stent, S., Cipolla, R. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016).
Henkel, E., Reiter, D.-I. R.: Digitale Fabrik – Stand der Anwendung heute und Ausblick auf die Weiterentwicklung, Magdeburg (2008).
Hui, J.: Object Detection: Speed and Accuracy Comparison (Faster R-CNN, R-FCN, SSD, FPN, RetinaNet and YOLOv3). In: Medium (2018), https://medium.com/@jonathan_hui/object-detection-speed-and-accuracy-comparison-faster-r-cnn-r-fcn-ssd-andyolo-5425656ae359, last accessed 2020/03/23.
Juhász, T., Schmucker, U.: From Engineering CAD to a Modelica Model: Structural Manipulation throughout a Translation Process, Magdeburg (2008).
Le, D.T.: Entwicklung eines modularisierten mobilen Manipulatorsystems für die flexible automatisierte Montage, Aachen: Shaker (2017).
Ludwig, C., Reiman, C.: Augmented Reality: Information im Fokus (2005).
Meyer, T.: Rolls-Royce nutzt Virtual und Augmented Reality bereits. In: Digitale Pioniere (2019). https://kem.industrie.de/top-news/top-beitrag/rolls-royce-nutzt-virtual-und-augmented-reality-bereits/ last accessed 2020/03/23.
Nozhnitsky, Yu.A.: The Problem of Ensuring Reliability of Gas Turbine Engines. In: IOP Conf. Ser.: Mater. Sci. Eng, vol. 302 (2018).
RE’FLEKT: Fünf Anwendungsfelder für Augmented Reality in Automotive, https://www.re-flekt.com/blog/automotive-augmented-reality, last accessed 2020/03/23.
Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In: Neural Information Processing Systems Conference, pp. 91–99, Vancouver (2015).
Seifert, S.: Augmented Reality - Die Erweiterung der Realität, In: unileipzig.de, http://www.informatik.uni-leipzig.de/~graebe/Texte/Seifert-14.pdf (2014), last accessed 2020/03/23.
Su, H., Qi, C., Li, Y., Guibas, L.: Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views (2019).
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Spanoudakis, K., Jonen, F., Borck, C. (2020). Creation of an Experimental Engineering Toolbox for the Digital Transformation of Manual Jet Engine Assembly. In: Schüppstuhl, T., Tracht, K., Henrich, D. (eds) Annals of Scientific Society for Assembly, Handling and Industrial Robotics. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-61755-7_26
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