Notice of Removal: Augmented Reality Based Data Improvement for the Planning of Aircraft Cabin Conversions

Deneke, Constantin; Moenck, Keno; Schüppstuhl, Thorsten

doi:10.1109/iciea49774.2020.9102113

Cited by 1 publication

(2 citation statements)

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“…During the cabin retrofit, for leased aircraft for example occurring approximately every five to seven years, big parts of the aircraft's cabin are removed and replaced by a partly or completely newly designed interior [1][2][3]. As this new cabin has to fit into the specific aircraft's body-its airframe-perfectly, planning the cabin as well as the retrofit process heavily relies on exact knowledge about the specific airframe [4]. While this scenario calls for an approach that currently can be frequently found in the literature under the term digital twin, aviation's special circumstances complicate the adaptation of said concepts and result in the need for an even more elaborate data handling effort.…”

Section: Introductionmentioning

confidence: 99%

“…This usually leads to extended time on the ground as conflicts are identified only during the attempt to install the new cabin, leading to impromptu required modifications and adaptations of the design or mounting. However, as each day spent on the ground to perform the retrofit is cost-intensive, the retrofit requires a sufficient planning basis as a foundation, ideally long before the aircraft arrives at the retrofit facility [4].…”

Section: Introduction To Aviation Retrofitmentioning

confidence: 99%

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Supporting Digital Twins for the Retrofit in Aviation by a Model-Driven Data Handling

Laukotka

Krause

2023

Systems

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Aviation is characterized by many stakeholders, long lifespans of its assets, and high requirements regarding safety, security, and documentation. To meet these requirements as well as customer needs, aircraft are regularly retrofitted with new cabins. During the planning and execution of this cabin retrofit, handling the needed and available data poses a challenge to the engineers. While much of the required data is available in some form, generally there is a lack of a digitally usable dataset of the specific aircraft—a virtual representation of the physical asset is missing. To support the implementation of such a digital twin and, thus, the overall process of retrofitting aircraft, an approach to model-driven data handling tailored to the unique circumstances and requirements of aviation is introduced. The methodology consists of a combination of systems engineering and data science techniques framed by an overarching procedure that iteratively creates and enhances a digitally accessible dataset of the relevant data, hence supporting the retrofit engineers by easing access to needed information. Besides the presentation of the research background and the methodology, a simplified example is shown, demonstrating the approach using abstracted but realistic information provided by partners from the industry.

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