---
_id: '58076'
abstract:
- lang: eng
text: This paper presents the concept of Information Circularity Assistance, which
provides decision support in the early stages of product creation for Circular
Economy. Engineers in strategic product planning need to proactively predict the
quantity, quality, and timing of secondary materials and returned components.
For example, products with high recycled content will only be economically sustainable
if the material is actually available in the future product life. Our assumption
is that Information Circularity Assistance enables decision makers to incorporate
insights from extreme data – high-volume, high-velocity, heterogeneous and distributed
data from the product life – into product creation through intelligent Digital
Twins. Artificial Intelligence can help to derive sustainable actions in favor
of circular products by processing extreme data and enriching it with expert knowledge.
The research contributes in three key dimensions. First, a comprehensive literature
review is conducted. This review covers concepts of intelligence in Scenario-Technique
for strategic product planning, Digital Twin-based analysis of extreme data and
relevant technologies from Data Science and Artificial Intelligence. In all areas,
the state of the art and emerging trends are identified. Secondly, the study identifies
information needs along the steps of the Scenario-Technique and information offerings
based on Digital Twins. The concept of Information Circularity Assistance results
from the coupling of these demands and offerings, extending the Scenario-Technique
beyond traditional expert-based methods. Third, we extend existing Digital Twin
methods used in circularity and discuss the deployment of Data Science and Artificial
Intelligence algorithms within the product creation process. Our approach uses
extreme data to provide a strategic advantage in optimizing product life cycle
planning, which is illustrated by two sample applications. The aim is to provide
Information Circularity Assistance that will support experienced product planners,
developers, and decision makers in the future.
alternative_title:
- Utilizing Artificial Intelligence, Scenario-Technique and Digital Twins to solve
challenges of product creation for Circular Economy
article_type: original
author:
- first_name: Iris
full_name: Gräßler, Iris
id: '47565'
last_name: Gräßler
orcid: 0000-0001-5765-971X
- first_name: Michael
full_name: Weyrich, Michael
last_name: Weyrich
- first_name: Jens
full_name: Pottebaum, Jens
id: '405'
last_name: Pottebaum
orcid: http://orcid.org/0000-0001-8778-2989
- first_name: Simon
full_name: Kamm, Simon
last_name: Kamm
citation:
ama: Gräßler I, Weyrich M, Pottebaum J, Kamm S. Information Circularity Assistance
based on extreme data. at - Automatisierungstechnik. 2025;73(1):3-21. doi:10.1515/auto-2024-0039
apa: Gräßler, I., Weyrich, M., Pottebaum, J., & Kamm, S. (2025). Information
Circularity Assistance based on extreme data. At - Automatisierungstechnik,
73(1), 3–21. https://doi.org/10.1515/auto-2024-0039
bibtex: '@article{Gräßler_Weyrich_Pottebaum_Kamm_2025, title={Information Circularity
Assistance based on extreme data}, volume={73}, DOI={10.1515/auto-2024-0039},
number={1}, journal={at - Automatisierungstechnik}, publisher={Walter de Gruyter
GmbH}, author={Gräßler, Iris and Weyrich, Michael and Pottebaum, Jens and Kamm,
Simon}, year={2025}, pages={3–21} }'
chicago: 'Gräßler, Iris, Michael Weyrich, Jens Pottebaum, and Simon Kamm. “Information
Circularity Assistance Based on Extreme Data.” At - Automatisierungstechnik
73, no. 1 (2025): 3–21. https://doi.org/10.1515/auto-2024-0039.'
ieee: 'I. Gräßler, M. Weyrich, J. Pottebaum, and S. Kamm, “Information Circularity
Assistance based on extreme data,” at - Automatisierungstechnik, vol. 73,
no. 1, pp. 3–21, 2025, doi: 10.1515/auto-2024-0039.'
mla: Gräßler, Iris, et al. “Information Circularity Assistance Based on Extreme
Data.” At - Automatisierungstechnik, vol. 73, no. 1, Walter de Gruyter
GmbH, 2025, pp. 3–21, doi:10.1515/auto-2024-0039.
short: I. Gräßler, M. Weyrich, J. Pottebaum, S. Kamm, At - Automatisierungstechnik
73 (2025) 3–21.
date_created: 2025-01-07T13:30:45Z
date_updated: 2025-02-15T09:41:54Z
department:
- _id: '152'
doi: 10.1515/auto-2024-0039
intvolume: ' 73'
issue: '1'
keyword:
- Scenario-Technique
- Artificial Intelligence
- Digital Twin
- Large Language Models
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
page: 3-21
publication: at - Automatisierungstechnik
publication_identifier:
issn:
- 0178-2312
- 2196-677X
publication_status: published
publisher: Walter de Gruyter GmbH
quality_controlled: '1'
status: public
title: Information Circularity Assistance based on extreme data
type: journal_article
user_id: '405'
volume: 73
year: '2025'
...
---
_id: '35464'
abstract:
- lang: eng
text: 'The digital transformation of organizations in the industrial sector is primarily
driven by the opportunity to increase productivity while simultaneously reducing
costs through integration into a cyber-physical system. One way to fully tap the
potential of a cyber-physical system is the concept of the digital twin, i.e.,
the real-time digital representation of machines and resources involved – including
human resources. The vision of representing humans by digital twins primarily
aims at increasing economic benefits. The digital twin of a human, however, cannot
be designed in a similar way to that of a machine. The human digital twin shall
rather enable humans to act within the cyber-physical system. It therefore offers
humans a power of control and the opportunity to provide feedback. The concept
of the digital twin is still in its infancy and raises many questions in particular
from an educational perspective. The contribution aims at answering the following
questions and refers to the example of team learning: Which and how much data
should and may the digital twin contain in order to support humans in their learning?
To what extent will humans be able to control and design their own learning? How
may skills, experiences, and social interactions of humans be represented in the
digital twin; their growth and further development, respectively? With cyber-physical
systems transcending corporate, national, and legal boundaries, what learning
culture will be the frame of reference for the involved organizations?'
author:
- first_name: ' Angelina'
full_name: Berisha-Gawlowski, Angelina
last_name: Berisha-Gawlowski
- first_name: Carina
full_name: Caruso, Carina
id: '23123'
last_name: Caruso
- first_name: Christian
full_name: Harteis, Christian
id: '27503'
last_name: Harteis
orcid: https://orcid.org/0000-0002-3570-7626
citation:
ama: 'Berisha-Gawlowski Angelina, Caruso C, Harteis C. The Concept of a Digital
Twin and Its Potential for Learning Organizations. In: Ifenthaler D, Hofhues S,
Egloffstein M, Helbig C, eds. Digital Transformation of Learning Organizations
. Springer; 2021:95–114. doi:10.1007/978-3-030-55878-9_6'
apa: Berisha-Gawlowski, Angelina, Caruso, C., & Harteis, C. (2021). The Concept
of a Digital Twin and Its Potential for Learning Organizations. In D. Ifenthaler,
S. Hofhues, M. Egloffstein, & C. Helbig (Eds.), Digital Transformation
of Learning Organizations (pp. 95–114). Springer. https://doi.org/10.1007/978-3-030-55878-9_6
bibtex: '@inbook{Berisha-Gawlowski_Caruso_Harteis_2021, place={Cham}, title={The
Concept of a Digital Twin and Its Potential for Learning Organizations}, DOI={10.1007/978-3-030-55878-9_6},
booktitle={Digital Transformation of Learning Organizations }, publisher={Springer},
author={Berisha-Gawlowski, Angelina and Caruso, Carina and Harteis, Christian},
editor={Ifenthaler, Dirk and Hofhues, Sandra and Egloffstein, Marc and Helbig,
Christian}, year={2021}, pages={95–114} }'
chicago: 'Berisha-Gawlowski, Angelina, Carina Caruso, and Christian Harteis. “The
Concept of a Digital Twin and Its Potential for Learning Organizations.” In Digital
Transformation of Learning Organizations , edited by Dirk Ifenthaler, Sandra
Hofhues, Marc Egloffstein, and Christian Helbig, 95–114. Cham: Springer, 2021.
https://doi.org/10.1007/978-3-030-55878-9_6.'
ieee: 'Angelina Berisha-Gawlowski, C. Caruso, and C. Harteis, “The Concept of a
Digital Twin and Its Potential for Learning Organizations,” in Digital Transformation
of Learning Organizations , D. Ifenthaler, S. Hofhues, M. Egloffstein, and
C. Helbig, Eds. Cham: Springer, 2021, pp. 95–114.'
mla: Berisha-Gawlowski, Angelina, et al. “The Concept of a Digital Twin and Its
Potential for Learning Organizations.” Digital Transformation of Learning Organizations
, edited by Dirk Ifenthaler et al., Springer, 2021, pp. 95–114, doi:10.1007/978-3-030-55878-9_6.
short: 'Angelina Berisha-Gawlowski, C. Caruso, C. Harteis, in: D. Ifenthaler, S.
Hofhues, M. Egloffstein, C. Helbig (Eds.), Digital Transformation of Learning
Organizations , Springer, Cham, 2021, pp. 95–114.'
date_created: 2023-01-09T10:38:42Z
date_updated: 2023-01-09T10:39:26Z
doi: 10.1007/978-3-030-55878-9_6
editor:
- first_name: Dirk
full_name: Ifenthaler, Dirk
last_name: Ifenthaler
- first_name: Sandra
full_name: Hofhues, Sandra
last_name: Hofhues
- first_name: Marc
full_name: Egloffstein, Marc
last_name: Egloffstein
- first_name: Christian
full_name: Helbig, Christian
last_name: Helbig
keyword:
- Digital twin
- Learning organization
- Change
- Team learning
- Professional development
language:
- iso: eng
page: ' 95–114'
place: Cham
publication: 'Digital Transformation of Learning Organizations '
publication_identifier:
eisbn:
- 978-3-030-55878-9
isbn:
- 978-3-030-55877-2
publication_status: published
publisher: Springer
status: public
title: The Concept of a Digital Twin and Its Potential for Learning Organizations
type: book_chapter
user_id: '86519'
year: '2021'
...