[{"status":"public","user_id":"405","volume":73,"page":"3-21","_id":"58076","publisher":"Walter de Gruyter GmbH","quality_controlled":"1","citation":{"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>.","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>","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>.","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} }","short":"I. Gräßler, M. Weyrich, J. Pottebaum, S. Kamm, At - Automatisierungstechnik 73 (2025) 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>","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>."},"oa":"1","date_updated":"2025-02-15T09:41:54Z","publication_status":"published","intvolume":"        73","article_type":"original","title":"Information Circularity Assistance based on extreme data","year":"2025","author":[{"full_name":"Gräßler, Iris","orcid":"0000-0001-5765-971X","last_name":"Gräßler","first_name":"Iris","id":"47565"},{"last_name":"Weyrich","first_name":"Michael","full_name":"Weyrich, Michael"},{"orcid":"http://orcid.org/0000-0001-8778-2989","last_name":"Pottebaum","first_name":"Jens","full_name":"Pottebaum, Jens","id":"405"},{"full_name":"Kamm, Simon","last_name":"Kamm","first_name":"Simon"}],"publication_identifier":{"issn":["0178-2312","2196-677X"]},"doi":"10.1515/auto-2024-0039","alternative_title":["Utilizing Artificial Intelligence, Scenario-Technique and Digital Twins to solve challenges of product creation for Circular Economy"],"main_file_link":[{"open_access":"1"}],"language":[{"iso":"eng"}],"abstract":[{"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.","lang":"eng"}],"issue":"1","publication":"at - Automatisierungstechnik","keyword":["Scenario-Technique","Artificial Intelligence","Digital Twin","Large Language Models"],"type":"journal_article","department":[{"_id":"152"}],"date_created":"2025-01-07T13:30:45Z"},{"abstract":[{"text":"New technologies and materials carry significant potential for sustainable production and use of products. As an example, Additive Manufacturing technologies and materials promise lightweight design and energy efficient use of parts. Exhausting the full potential requires: a) consideration of uncertainties with respect to future capabilities, and b) upgradeable design guidelines to cover advancements consistently. The proposed approach merges concepts of Design-for-X with foresight algorithms of Scenario-Technique to derive actionable knowledge. It is validated by an application in the field of Additive Manufacturing, namely Metal Fused Deposition Modelling. Engineers benefit from the intuitive access to heterogeneous types of sustainability related information.","lang":"eng"}],"publication":"17th CIRP Conference on Intelligent Computation in Manufacturing Engineering","type":"conference","keyword":["Design-for-X","Scenario-Technique","sustainability","uncertainty","Life-Cycle Engineering","Additive Manufacturing","Circular Economy"],"department":[{"_id":"152"},{"_id":"741"}],"date_created":"2023-08-08T07:42:04Z","publication_status":"published","date_updated":"2024-11-21T10:13:30Z","intvolume":"       126","title":"Handling of uncertainties in the design of sustainable Additive Manufacturing products by merging Design-for-X and Scenario-Technique","year":"2024","author":[{"id":"47565","orcid":"0000-0001-5765-971X","last_name":"Gräßler","first_name":"Iris","full_name":"Gräßler, Iris"},{"last_name":"Mozgova","first_name":"Iryna","full_name":"Mozgova, Iryna","id":"95903"},{"id":"405","last_name":"Pottebaum","first_name":"Jens","orcid":"http://orcid.org/0000-0001-8778-2989","full_name":"Pottebaum, Jens"},{"id":"44204","first_name":"Manuel","last_name":"Ott","full_name":"Ott, Manuel"},{"full_name":"Jung, Philipp","first_name":"Philipp","last_name":"Jung"},{"first_name":"Philipp","last_name":"Hesse","full_name":"Hesse, Philipp","id":"60633"}],"doi":"10.1016/j.procir.2024.08.238","main_file_link":[{"open_access":"1"}],"series_title":"Procedia CIRP","language":[{"iso":"eng"}],"quality_controlled":"1","project":[{"name":"BIKINI: BIKINI - Bionik und KI für nachhaltige Integration von Produktentwicklung für einen ressourceneffizienten Leichtbau","_id":"519"}],"citation":{"short":"I. Gräßler, I. Mozgova, J. Pottebaum, M. Ott, P. Jung, P. Hesse, in: 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering, Elsevier, 2024, pp. 549–554.","chicago":"Gräßler, Iris, Iryna Mozgova, Jens Pottebaum, Manuel Ott, Philipp Jung, and Philipp Hesse. “Handling of Uncertainties in the Design of Sustainable Additive Manufacturing Products by Merging Design-for-X and Scenario-Technique.” In <i>17th CIRP Conference on Intelligent Computation in Manufacturing Engineering</i>, 126:549–54. Procedia CIRP. Elsevier, 2024. <a href=\"https://doi.org/10.1016/j.procir.2024.08.238\">https://doi.org/10.1016/j.procir.2024.08.238</a>.","ieee":"I. Gräßler, I. Mozgova, J. Pottebaum, M. Ott, P. Jung, and P. Hesse, “Handling of uncertainties in the design of sustainable Additive Manufacturing products by merging Design-for-X and Scenario-Technique,” in <i>17th CIRP Conference on Intelligent Computation in Manufacturing Engineering</i>, Gulf of Naples, 2024, vol. 126, pp. 549–554, doi: <a href=\"https://doi.org/10.1016/j.procir.2024.08.238\">10.1016/j.procir.2024.08.238</a>.","apa":"Gräßler, I., Mozgova, I., Pottebaum, J., Ott, M., Jung, P., &#38; Hesse, P. (2024). Handling of uncertainties in the design of sustainable Additive Manufacturing products by merging Design-for-X and Scenario-Technique. <i>17th CIRP Conference on Intelligent Computation in Manufacturing Engineering</i>, <i>126</i>, 549–554. <a href=\"https://doi.org/10.1016/j.procir.2024.08.238\">https://doi.org/10.1016/j.procir.2024.08.238</a>","bibtex":"@inproceedings{Gräßler_Mozgova_Pottebaum_Ott_Jung_Hesse_2024, series={Procedia CIRP}, title={Handling of uncertainties in the design of sustainable Additive Manufacturing products by merging Design-for-X and Scenario-Technique}, volume={126}, DOI={<a href=\"https://doi.org/10.1016/j.procir.2024.08.238\">10.1016/j.procir.2024.08.238</a>}, booktitle={17th CIRP Conference on Intelligent Computation in Manufacturing Engineering}, publisher={Elsevier}, author={Gräßler, Iris and Mozgova, Iryna and Pottebaum, Jens and Ott, Manuel and Jung, Philipp and Hesse, Philipp}, year={2024}, pages={549–554}, collection={Procedia CIRP} }","ama":"Gräßler I, Mozgova I, Pottebaum J, Ott M, Jung P, Hesse P. Handling of uncertainties in the design of sustainable Additive Manufacturing products by merging Design-for-X and Scenario-Technique. In: <i>17th CIRP Conference on Intelligent Computation in Manufacturing Engineering</i>. Vol 126. Procedia CIRP. Elsevier; 2024:549-554. doi:<a href=\"https://doi.org/10.1016/j.procir.2024.08.238\">10.1016/j.procir.2024.08.238</a>","mla":"Gräßler, Iris, et al. “Handling of Uncertainties in the Design of Sustainable Additive Manufacturing Products by Merging Design-for-X and Scenario-Technique.” <i>17th CIRP Conference on Intelligent Computation in Manufacturing Engineering</i>, vol. 126, Elsevier, 2024, pp. 549–54, doi:<a href=\"https://doi.org/10.1016/j.procir.2024.08.238\">10.1016/j.procir.2024.08.238</a>."},"oa":"1","status":"public","conference":{"location":"Gulf of Naples","start_date":"2023-07-11","name":"17th CIRP Conference on Intelligent Computation in Manufacturing Engineering","end_date":"2023-07-14"},"user_id":"405","volume":126,"page":"549-554","_id":"46451","publisher":"Elsevier"},{"oa":"1","citation":{"mla":"Weber, Jens, et al. “System Thinking: Crafting Scenarios for Prescriptive Analytics.” <i>Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) Co-Located with Konvens 2014</i>, edited by Hanmin Jung et al., vol. 1292, CEUR-WS.org, 2014.","ama":"Weber J, Minhee C, Lee M, Song S, Geierhos M, Jung H. System Thinking: Crafting Scenarios for Prescriptive Analytics. In: Jung H, Mandl T, Womsen-Hacker C, Xu S, eds. <i>Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) Co-Located with Konvens 2014</i>. Vol 1292. CEUR Workshop Proceedings. CEUR-WS.org; 2014.","bibtex":"@inproceedings{Weber_Minhee_Lee_Song_Geierhos_Jung_2014, series={CEUR Workshop Proceedings}, title={System Thinking: Crafting Scenarios for Prescriptive Analytics}, volume={1292}, booktitle={Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) co-located with Konvens 2014}, publisher={CEUR-WS.org}, author={Weber, Jens and Minhee, Cho and Lee, Mikyoung and Song, Sa-kwang and Geierhos, Michaela and Jung, Hanmin}, editor={Jung, Hanmin and Mandl, Thomas and Womsen-Hacker, Christa and Xu, ShuoEditors}, year={2014}, collection={CEUR Workshop Proceedings} }","apa":"Weber, J., Minhee, C., Lee, M., Song, S., Geierhos, M., &#38; Jung, H. (2014). System Thinking: Crafting Scenarios for Prescriptive Analytics. In H. Jung, T. Mandl, C. Womsen-Hacker, &#38; S. Xu (Eds.), <i>Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) co-located with Konvens 2014</i> (Vol. 1292). Hildesheim, Germany: CEUR-WS.org.","ieee":"J. Weber, C. Minhee, M. Lee, S. Song, M. Geierhos, and H. Jung, “System Thinking: Crafting Scenarios for Prescriptive Analytics,” in <i>Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) co-located with Konvens 2014</i>, Hildesheim, Germany, 2014, vol. 1292.","short":"J. Weber, C. Minhee, M. Lee, S. Song, M. Geierhos, H. Jung, in: H. Jung, T. Mandl, C. Womsen-Hacker, S. Xu (Eds.), Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) Co-Located with Konvens 2014, CEUR-WS.org, 2014.","chicago":"Weber, Jens, Cho Minhee, Mikyoung Lee, Sa-kwang Song, Michaela Geierhos, and Hanmin Jung. “System Thinking: Crafting Scenarios for Prescriptive Analytics.” In <i>Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) Co-Located with Konvens 2014</i>, edited by Hanmin Jung, Thomas Mandl, Christa Womsen-Hacker, and Shuo Xu, Vol. 1292. CEUR Workshop Proceedings. CEUR-WS.org, 2014."},"quality_controlled":"1","_id":"1134","publisher":"CEUR-WS.org","volume":1292,"editor":[{"first_name":"Hanmin","last_name":"Jung","full_name":"Jung, Hanmin"},{"first_name":"Thomas","last_name":"Mandl","full_name":"Mandl, Thomas"},{"full_name":"Womsen-Hacker, Christa","last_name":"Womsen-Hacker","first_name":"Christa"},{"full_name":"Xu, Shuo","last_name":"Xu","first_name":"Shuo"}],"user_id":"42496","conference":{"end_date":"2014-10-07","location":"Hildesheim, Germany","start_date":"2014-10-06","name":"First International Workshop on Patent Mining and Its Applications (IPaMin 2014)"},"status":"public","date_created":"2018-01-30T15:27:08Z","department":[{"_id":"36"},{"_id":"1"},{"_id":"579"}],"keyword":["Standardized Influential Factors","Prescriptive Analytics","Role Model Group","Scenario Technique"],"type":"conference","publication":"Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) co-located with Konvens 2014","abstract":[{"text":"This paper focuses on the first step in combining prescriptive analytics with scenario techniques in order to provide strategicdevelopment after the useof InSciTe, a data prescriptive analytics application. InSciTe supports the improvement of researchers‘ individual performance by recommending new research directions. Standardized influential factors are presented as a foundation for automated scenario modelling such as the prototypical report generation function of InSciTe. Additionally, a use-case is shown which validatesthe potential of the standardized influential factors for raw scenario development.","lang":"eng"}],"series_title":"CEUR Workshop Proceedings","language":[{"iso":"eng"}],"main_file_link":[{"url":"http://ceur-ws.org/Vol-1292/ipamin2014_paper1.pdf","open_access":"1"}],"author":[{"first_name":"Jens","last_name":"Weber","full_name":"Weber, Jens"},{"full_name":"Minhee, Cho","first_name":"Cho","last_name":"Minhee"},{"full_name":"Lee, Mikyoung","first_name":"Mikyoung","last_name":"Lee"},{"last_name":"Song","first_name":"Sa-kwang","full_name":"Song, Sa-kwang"},{"full_name":"Geierhos, Michaela","first_name":"Michaela","last_name":"Geierhos","orcid":"0000-0002-8180-5606","id":"42496"},{"first_name":"Hanmin","last_name":"Jung","full_name":"Jung, Hanmin"}],"publication_identifier":{"issn":["16130073"]},"title":"System Thinking: Crafting Scenarios for Prescriptive Analytics","year":"2014","intvolume":"      1292","publication_status":"published","date_updated":"2022-01-06T06:50:59Z"}]