Fehlerdiagnose mit Virtual Reality trainieren – Entwicklung und Erprobung einer virtuellen Offshore-Windenergieanlage

Kapp, Felix; Matthes, Nadine; Kruse, Linda; Niebeling, Moritz; Spangenberger, Pia

doi:10.1007/s41449-022-00316-8

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Digital twins driven by sensor data can be used to quantify the remaining lifetime and inform control actions or maintenance decisions (Branlard et al, 2020;Pettas et al, 2018;Rinker et al, 2018). Maintenance can also be made easier or more effective through the use of virtual reality (VR) for maintenance planning, augmented reality (AR) to help technicians identify equipment, online manuals accessed using speech-recognition systems, inspection by unmanned aerial vehicles (UAVs), or the use of robots to carry out repairs, as well as many other tools (see, for example, Kapp et al, 2022;Eggert et al, 2020).…”

Section: Digital Businessesmentioning

confidence: 99%

Grand challenges in the digitalisation of wind energy

Clifton

Barber

Bray³

et al. 2023

Wind Energ. Sci.

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Abstract. The availability of large amounts of data is starting to impact how the wind energy community works. From turbine design to plant layout, construction, commissioning, and maintenance and operations, new processes and business models are springing up. This is the process of digitalisation, and it promises improved efficiency and greater insight, ultimately leading to increased energy capture and significant savings for wind plant operators, thus reducing the levelised cost of energy. Digitalisation is also impacting research, where it is both easing and speeding up collaboration, as well as making research results more accessible. This is the basis for innovations that can be taken up by end users. But digitalisation faces barriers. This paper uses a literature survey and the results from an expert elicitation to identify three common industry-wide barriers to the digitalisation of wind energy. Comparison with other networked industries and past and ongoing initiatives to foster digitalisation show that these barriers can only be overcome by wide-reaching strategic efforts, and so we see these as “grand challenges” in the digitalisation of wind energy. They are, first, creating FAIR data frameworks; secondly, connecting people and data to foster innovation; and finally, enabling collaboration and competition between organisations. The grand challenges in the digitalisation of wind energy thus include a mix of technical, cultural, and business aspects that will need collaboration between businesses, academia, and government to solve. Working to mitigate them is the beginning of a dynamic process that will position wind energy as an essential part of a global clean energy future.

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Section: Digital Businessesmentioning

confidence: 99%

Grand challenges in the digitalisation of wind energy

Clifton

Barber

Bray³

et al. 2023

Wind Energ. Sci.

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“…Furthermore, the criteria were supplemented with additional quality method-specific criteria. Thus, in the following criteria are to be applied: Organizational techniques (1), technology evaluating techniques (2), behavioral techniques (3), purpose (4), presentation of graphical results (5), required qualification of employees (6), impact on the quality (7), focus on the process (8), data (9) and workplace (10) as well as complexity of use (11), time required for implementation (12) as well as the criterion solo or team work (13). An excerpt of these can be seen in table 1.…”

Section: Arim -Potential Analysis In Practicementioning

confidence: 99%

Procedure for the implementation of VR/AR learning scenarios for method training - Presentation of the Assisted Reality Implementation Model (ARIM).

Karcher

Arnold

Prinz

et al. 2022

Preprint

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Virtual - and Augmented Reality (VR/AR) based assistance systems represent a growing technology approach for the sustainable communication of quality methods for further education offers. To create virtual learning environments as standardized and efficient as possible, a uniform approach is required. This paper focuses on the development of the Assisted Reality Implementation Model (ARIM) for the selection of Lean Management and Six Sigma quality methods that are suitable to be taught using augmented and virtual reality learning environments. Furthermore, the ARIM enables meaningful guidance for the implementation of the virtual learning environments, as well as subsequent validation. The model will be applied and evaluated within the research project WILLEN.

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Fehlerdiagnose mit Virtual Reality trainieren – Entwicklung und Erprobung einer virtuellen Offshore-Windenergieanlage

Cited by 2 publications

References 14 publications

Grand challenges in the digitalisation of wind energy

Grand challenges in the digitalisation of wind energy

Procedure for the implementation of VR/AR learning scenarios for method training - Presentation of the Assisted Reality Implementation Model (ARIM).

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