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Graph-Based Model for Context-Aware Maintenance Assistance with Augmented Reality and 3D Visualization

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Advances in Through-life Engineering Services

Part of the book series: Decision Engineering ((DECENGIN))

Abstract

The benefits of augmented reality applications in maintenance are widely known and since high-performance smart devices are the common standard for mobile devices, the actual preconditions for the usage of such applications seem promising. Problems emerge whenever service is to be conducted in an area of banned photography. Using a smart device with a camera is either simply not allowed, or the internal camera has to be pasted over to allow entrance into the restricted areas. Either way, the technician still relies on his maintenance assistant system to provide useful information if he does not want to go back to pen and paper. In this article a concept is elaborated that offers context-sensitive guidance, a highly dynamic data model and different views, depending on the availability of an internal camera and/or restrictions of the work environment. The approach presented was implemented and validated under laboratory conditions with a complex hydraulic system as a demonstrator machine. The prototype will be the foundation of an industrial case study concerning the combination of IoT enabled machinery and smart devices in maintenance later this year.

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Correspondence to Mario Wolf .

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Abramovici, M., Wolf, M., Neges, M. (2017). Graph-Based Model for Context-Aware Maintenance Assistance with Augmented Reality and 3D Visualization. In: Redding, L., Roy, R., Shaw, A. (eds) Advances in Through-life Engineering Services. Decision Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-49938-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-49938-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49937-6

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