Výsledky vyhledávání - "Rokoss, Alexander"

Akademický článek

Case study on delivery time determination using a machine learning approach in small batch production companies.

Autor: Rokoss, Alexander¹ (AUTHOR) alexander.rokoss@leuphana.de, Syberg, Marius² (AUTHOR), Tomidei, Laura³ (AUTHOR), Hülsing, Christian¹ (AUTHOR), Deuse, Jochen^2,3 (AUTHOR), Schmidt, Matthias¹ (AUTHOR)

Publikováno v: Journal of Intelligent Manufacturing. Dec2024, Vol. 35 Issue 8, p3937-3958. 22p.

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KI-Kanban-Behälter:Mobile, dezentrale Logistikdatenerfassung mittels Edge-ML

Autor: Rokoss, Alexander, Popkes, Lennart, Kramer, Kathrin, Green, Thorben, Schmidt, Matthias

Publikováno v: Rokoss, A, Popkes, L, Kramer, K, Green, T & Schmidt, M 2023, ' KI-Kanban-Behälter : Mobile, dezentrale Logistikdatenerfassung mittels Edge-ML ', ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, Jg. 118, Nr. 1-2, S. 59-63 . https://doi.org/10.1515/zwf-2023-1004

Mit dem Kanban-Verfahren gesteuerte Produktionssysteme nutzen heute elektronische Unterstützung zur Verfolgung einzelner Behälter, um datenbasiert Logistikprozesse zu verbessern. Dieser Beitrag stellt eine alternative technische Auslegung vor. Es f

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https://www.degruyter.com/document/doi/10.1515/zwf-2023-1004/html

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A Systematic Literature Review of Machine Learning Approaches for the Prediction of Delivery Dates

Autor: Maier, Janine Tatjana, Rokoss, Alexander, Green, Thorben, Brkovic, Nikola, Schmidt, Matthias, Herberger, David, Hübner, Marco

Publikováno v: Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

Manufacturing companies tend to use standardized delivery times. The actual delivery times requested by the customers and the current capacity utilization of the production are often not taken into account. Therefore, such a simplification likely res

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::252760626b9809f3401a715d556038f3
https://www.repo.uni-hannover.de/handle/123456789/12255

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Application of Machine Learning on Transport Spot Rate Prediction in the Recycling Industry

Autor: Green, Thorben, Rokoss, Alexander, Kramer, Kathrin, Schmidt, Matthias, Herberger, David, Hübner, Marco

Publikováno v: Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

The transport spot rate in trucking logistics is an important factor for market participants in the recycling industry. Knowledge about the current spot rate is essential for operational decision-making in price negotiations between brokers and shipp

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Akademický článek

KI-Kanban-Behälter: Mobile, dezentrale Logistikdatenerfassung mittels Edge-ML.

Autor: Rokoss, Alexander, Popkes, Lennart, Kramer, Kathrin, Green, Thorben, Schmidt, Matthias

Publikováno v: ZWF Zeitschrift fur Wirtschaftlichen Fabrikbetrieb; Feb2023, Vol. 118 Issue 1/2, p59-63, 5p

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Outperformed by a Computer? - Comparing Human Decisions to Reinforcement Learning Agents, Assigning Lot Sizes in a Learning Factory:11th Conference on Learning Factories, CLF2021

Autor: Voß, Thomas, Rokoss, Alexander, Maier, Janine Tatjana, Schmidt, Matthias, Heger, Jens

Publikováno v: Voß, T, Rokoss, A, Maier, J T, Schmidt, M & Heger, J 2021 ' Outperformed by a Computer?-Comparing Human Decisions to Reinforcement Learning Agents, Assigning Lot Sizes in a Learning Factory : 11th Conference on Learning Factories, CLF2021 ' SSRN, Elsevier Inc., Rochester . https://doi.org/10.2139/ssrn.3859196

Given the fact that some products in the production system require larger cycle times and a setup process during production, the application of different lot sizes might be beneficial regarding economic and logistic key performance indicators. Maximi

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http://fox.leuphana.de/portal/de/publications/outperformed-by-a-computer--comparing-human-decisions-to-reinforcement-learning-agents-assigning-lot-sizes-in-a-learning-factory(f27161b0-fb17-4f1e-a53e-8d1d76eb232d).html

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Using Digitalization As An Enabler For Changeability In Production Systems In A Learning Factory Environment

Autor: Rokoss, Alexander, Schmidt, Matthias

Publikováno v: Rokoss, A & Schmidt, M 2021, Using Digitalization As An Enabler For Changeability In Production Systems In A Learning Factory Environment . in D Herberger & M Hübner (eds), Conference on Production Systems and Logistics : International Conference, CPSL 2021, Digital Event hosted via publish-Ing; August 10-11, 2021; Proceedings . Proceedings of the ... Conference on Production Systems and Logistics, vol. 2, publish-Ing., Offenburg, pp. 730-739, 2nd Conference on Production Systems and Logistics-CPSL 2021, 10.08.21 . https://doi.org/10.15488/11279

Existing as well as new production systems need to adapt to meet increasing requirements of global, volatile markets. Companies aim to keep their production systems physically changeable while at the same time raise their level of digitalization. The

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3697::4f005d567f579243c8d5ddefc217ec81
https://www.repo.uni-hannover.de/handle/123456789/11315

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A learning factory approach on machine learning in production companies:How a learning factory approach can help to increase the understanding of the application of machine learning on production planning and control tasks

Autor: Rokoss, Alexander, Kramer, Kathrin, Schmidt, Matthias

Publikováno v: Rokoss, A, Kramer, K & Schmidt, M 2021, A learning factory approach on machine learning in production companies : How a learning factory approach can help to increase the understanding of the application of machine learning on production planning and control tasks . in W Sihn & S Schlund (eds), Competence development and learning assistance systems for the data-driven future . Schriftenreihe der Wissenschaftlichen Gesellschaft für Arbeits-und Betriebsorganisation (WGAB) e.V., GITO Verlag, Berlin, pp. 125-142 . https://doi.org/10.30844/wgab_2021

Technological progress and increasing digitalization offer many opportunities to production companies, but also continually present them with new challenges. The automation of processes is progressing in manufacturing areas and technical support syst

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3697::3144151c1412ea8b03e06cc29f3c1e00
https://www.mendeley.com/catalogue/e337b225-7b35-3339-9319-04b66d08ee4e/

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Do We Really Know The Benefit Of Machine Learning In Production Planning And Control? A Systematic Review Of Industry Case Studies

Autor: Kramer, Kathrin, Rokoss, Alexander, Schmidt, Matthias

Publikováno v: Kramer, K, Rokoss, A & Schmidt, M 2021, Do We Really Know The Benefit Of Machine Learning In Production Planning And Control? A Systematic Review Of Industry Case Studies . in D Herberger & M Hübner (eds), Conference on Production Systems and Logistics : International Conference, CPSL 2021, Digital Event hosted via publish-Ing; August 10-11, 2021; Proceedings . Proceedings of the ... Conference on Production Systems and Logistics, vol. 2, publish-Ing., Offenburg, pp. 223-233, 2nd Conference on Production Systems and Logistics (CPSL 2021), 10.08.21 . https://doi.org/10.15488/11296

The field of machine learning (ML) is of specific interest for production companies as it displays a perspective to handle the increased complexity within their production planning and control (PPC) processes in an economic and ecologic effective as

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3697::7877459232738beabc00f1f7c80978d8
https://www.repo.uni-hannover.de/handle/123456789/11315

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