Investigation of an Automated Potting Process for High Volume Insert Assembly in Honeycomb Structures

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Event
AeroTech® Digital Summit
Authors Abstract
Content
Threaded, potted inserts are commonly used as a standard connecting element for sandwich components, which are used for aircraft interior. Since they often offer the only detachable connection, they are used in very high quantities. To ensure a material bond between the inserts and the honeycomb structure, the joint is filled with adhesive. Despite the high number of inserts, this process is performed manually. Recent research has shown new approaches for automated gripping and placement of the inserts by an industrial robot that yield high potential for cost savings and increased productivity. Automated adhesive insertion, so-called potting, has not been considered so far but is an essential contribution to the full automation of the entire process chain. The amount of adhesive varies depending on the type of insert and its position on the honeycomb structure. During the potting process, it is also mandatory to prevent air inclusions, to fulfill safety requirements in the aviation industry. This paper presents an approach for automated potting to further increase the degree of automation during sandwich panel production. First, the range of insert types is analyzed and the joint geometries are investigated. Based on the derived requirements, an automation concept is introduced and a parameter study is carried out. Optimal parameters are derived which can be used for process control. Finally, the overall process capability is shown and evaluated using a flexible, automated system.
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DOI
https://doi.org/10.4271/2022-01-0010
Pages
13
Citation
Kalscheuer, F., Müller, T., Gierecker, J., and Schüppstuhl, T., "Investigation of an Automated Potting Process for High Volume Insert Assembly in Honeycomb Structures," SAE Int. J. Adv. & Curr. Prac. in Mobility 4(3):994-1006, 2022, https://doi.org/10.4271/2022-01-0010.
Additional Details
Publisher
Published
Mar 8, 2022
Product Code
2022-01-0010
Content Type
Journal Article
Language
English