{"publication_identifier":{"issn":["0178-2312","2196-677X"]},"publication_status":"published","intvolume":"        73","page":"3-21","volume":73,"article_type":"original","publisher":"Walter de Gruyter GmbH","department":[{"_id":"152"}],"date_created":"2025-01-07T13:30:45Z","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."}],"keyword":["Scenario-Technique","Artificial Intelligence","Digital Twin","Large Language Models"],"title":"Information Circularity Assistance based on extreme data","user_id":"405","alternative_title":["Utilizing Artificial Intelligence, Scenario-Technique and Digital Twins to solve challenges of product creation for Circular Economy"],"status":"public","date_updated":"2025-01-07T13:40:54Z","citation":{"short":"I. Gräßler, M. Weyrich, J. Pottebaum, S. Kamm, At - Automatisierungstechnik 73 (2025) 3–21.","bibtex":"@article{Gräßler_Weyrich_Pottebaum_Kamm_2025, title={Information Circularity Assistance based on extreme data}, volume={73}, DOI={<a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>}, 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} }","ama":"Gräßler I, Weyrich M, Pottebaum J, Kamm S. Information Circularity Assistance based on extreme data. <i>at - Automatisierungstechnik</i>. 2025;73(1):3-21. doi:<a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>","ieee":"I. Gräßler, M. Weyrich, J. Pottebaum, and S. Kamm, “Information Circularity Assistance based on extreme data,” <i>at - Automatisierungstechnik</i>, vol. 73, no. 1, pp. 3–21, 2025, doi: <a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>.","mla":"Gräßler, Iris, et al. “Information Circularity Assistance Based on Extreme Data.” <i>At - Automatisierungstechnik</i>, vol. 73, no. 1, Walter de Gruyter GmbH, 2025, pp. 3–21, doi:<a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>.","apa":"Gräßler, I., Weyrich, M., Pottebaum, J., &#38; Kamm, S. (2025). Information Circularity Assistance based on extreme data. <i>At - Automatisierungstechnik</i>, <i>73</i>(1), 3–21. <a href=\"https://doi.org/10.1515/auto-2024-0039\">https://doi.org/10.1515/auto-2024-0039</a>","chicago":"Gräßler, Iris, Michael Weyrich, Jens Pottebaum, and Simon Kamm. “Information Circularity Assistance Based on Extreme Data.” <i>At - Automatisierungstechnik</i> 73, no. 1 (2025): 3–21. <a href=\"https://doi.org/10.1515/auto-2024-0039\">https://doi.org/10.1515/auto-2024-0039</a>."},"publication":"at - Automatisierungstechnik","type":"journal_article","issue":"1","quality_controlled":"1","doi":"10.1515/auto-2024-0039","_id":"58076","year":"2025","author":[{"first_name":"Iris","id":"47565","orcid":"0000-0001-5765-971X","last_name":"Gräßler","full_name":"Gräßler, Iris"},{"first_name":"Michael","full_name":"Weyrich, Michael","last_name":"Weyrich"},{"orcid":"http://orcid.org/0000-0001-8778-2989","full_name":"Pottebaum, Jens","last_name":"Pottebaum","first_name":"Jens","id":"405"},{"first_name":"Simon","full_name":"Kamm, Simon","last_name":"Kamm"}],"language":[{"iso":"eng"}]}