Post assembly quality inspection using multimodal sensing in aircraft manufacturing

Nicola Mosca; Vito Renò; Massimiliano Nitti; Cosimo Patruno; Ettore Stella

doi:10.1117/12.2594104

20 June 2021 Post assembly quality inspection using multimodal sensing in aircraft manufacturing

Nicola Mosca, Vito Renò, Massimiliano Nitti, Cosimo Patruno, Ettore Stella

Proceedings Volume 11785, Multimodal Sensing and Artificial Intelligence: Technologies and Applications II; 117850X (2021) https://doi.org/10.1117/12.2594104
Event: SPIE Optical Metrology, 2021, Online Only

Abstract

Contactless, non-destructive testing has always been an important pillar in crucial tasks performed in industrial applications, including post-assembly testing oriented toward aircraft manufacturing. This work will examine the topic from the point of view of the quality check for the lining of aircraft interiors, such as sidewalls and hatracks, with the aim of improving safety of operation and comfort during flights, using an automatic approach guided by the usage of computer vision system. In particular, it will present a multimodal approach using a 3d snapshot sensor and a color camera, for identifying defects and anomalies that belong to two distinct categories, such as geometrical and surface defects, where, in the aircraft manufacturing sectors, due to the low-volume production, when compared with the automotive industry, such quality check operation tasks are still done manually, with a low level of automation. The proposed approach is showing potential and has been demonstrated on a proof-of-concept system prototype funded through a European Commission Horizon 2020 research project under the Clean Sky 2 umbrella aimed at the growth of the aviation sector.

Conference Presentation

Citation Download Citation

Nicola Mosca, Vito Renò, Massimiliano Nitti, Cosimo Patruno, and Ettore Stella "Post assembly quality inspection using multimodal sensing in aircraft manufacturing", Proc. SPIE 11785, Multimodal Sensing and Artificial Intelligence: Technologies and Applications II, 117850X (20 June 2021); https://doi.org/10.1117/12.2594104

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