Jun.-Prof. Dr.-Ing. Sebastian Lang
Jun.-Prof. Dr.-Ing. Sebastian Lang
Junior Professorship for »Artificial Intelligence (AI) - Application in Production and Logistics«
Current projects
AI Engineering - An interdisciplinary, project-oriented bachelor's degree program with a focus on artificial intelligence and engineering.
Duration: 01.12.2021 bis 30.11.2025
AI Engineering (AiEng) encompasses the systematic design, development, integration and operation of solutions based on artificial intelligence (AI) using engineering methods as a model. At the same time, AiEng builds a bridge between basic research on AI methods and the engineering sciences and makes the use of AI systematically accessible and available there. The project focuses on the nationwide development of an "AI Engineering" Bachelor's degree program, which combines the training of AI methods, models and technologies with those of engineering sciences. AiEng is to be designed as a cooperative study program between Otto von Guericke University (OVGU) Magdeburg and the four universities in Saxony-Anhalt: Anhalt University of Applied Sciences, Harz University of Applied Sciences, Magdeburg-Stendal University of Applied Sciences and Merseburg University of Applied Sciences. The interdisciplinary degree program will enable students to develop AI systems and services in the industrial environment and beyond and to provide holistic support for the associated engineering process - from problem analysis to commissioning and maintenance / servicing. The AiEng curriculum provides comprehensive AI training, supplemented by basic engineering training and in-depth training in a selected application domain. In order to achieve a symbiosis of AI and engineering education, a new action-oriented framework is developed and taught, which describes the complete engineering process of AI solutions and methodically supports all phases. AIEng is characterized by a cross-module interlocking of teaching and learning content within a semester as well as by a cross-faculty and cross-university tandem teaching concept and pursues a student-centered didactic concept, which is supported by many practice-oriented (team) projects and a wide range of Open Educational Resources (OERs) with an (e)-tutor program.
Completed projects
24401_ SENECA - Development of a self-learning decision support system for real-time order sequencing and machine scheduling
Duration: 01.04.2020 bis 31.03.2022
The research project SENECA pursues the development of a self-learning decision support system for real-time order sequencing and machine scheduling. The research question is how machine learning (ML) methods must be applied in order to calculate admissible solutions with sufficient quality for order sequencing and machine allocation problems in real time. Various ML methods are to be investigated with regard to their applicability for order sequencing and machine allocation planning. Due to the highly dynamic nature of modern production systems and the resulting planning uncertainty, it is expected that production sequence planning in particular will benefit from ML-based, real-time capable and adaptive decision support systems. ML algorithms are currently primarily used for regression and classification problems. Their direct use for calculating optimization problems has hardly been researched and industrial applications are not yet known. The technical objective of the project is to develop a software and hardware prototype that supports decision-makers in production planning and control. The technical challenges relate in particular to aspects of production and application-specific design. On the one hand, a high level of user-friendliness is important. This implies, among other things, that humans are always the final decision-making authority. The system should be able to continuously improve itself with human expertise. On the other hand, the assistance system must be designed in such a way that the real-time capability of the solution processes is fully utilized. Proposed order sequences and machine assignments must be able to be transferred from production planning to production control at short notice.
Development of a Bologna-based Master Curriculum in Resource Efficient Production Logistics (ProdLog)
Duration: 01.12.2017 bis 15.10.2021
ProdLog addresses the issue of a weak industrial sector in Kazakhstan, Kyrgyzstan and Russian Federation and focuses on enabling universities to gain and provide a profound and holistic knowledge on planning and operating sustainable production processes. For that purpose a bologna-based master curriculum with 18 modules in resource efficient production logistics will be developed and implemented in six universities of the partner countries. The academic staff will be trained with innovative teaching methods in the learning factory "Technology centre for production and logistics systems PULS" and equipped with state of the art logistics laboratories. By means of that, the understanding of logistics shall be widened - away from transport logistics to a systemic and interdisciplinary approach of applicant-oriented education, challenges with economical, political and social problems of our society.
Lastenraddepot - "Bürger*innen- und Verkehrsgerechte Implementierung von Innenstadtdepots für Lastenfahrräder"
Duration: 01.09.2017 bis 30.11.2019
Lastenräder sind eine nachhaltige Alternative für den Transport von Waren in Städten. Sie haben das Potenzial zur Substitution von 25% der heutigen innerstädtischen Lieferfahrten und können so zu CO2-Einsparungen und einer höheren Lebensqualität in Städten beitragen. Das Einrichten von Innenstadtdepots für Lastenräder ermöglicht die Lagerung und den Umschlag von Waren für die anschließende Verteilung per Lastenrad in der Stadt. In dem interdisziplinären Projekt "Lastenraddepot" wird ein modellhafter Leitfaden zur Implementierung von Innenstadtdepots entwickelt. Der Fokus liegt sowohl auf logistischen Anforderungen, der Gewährleistung des Verkehrsflusses und einer hohen Akzeptanz durch Stakeholder. Es werden Aspekte wie Standortfragen, die Wirkung eines hohen Lastenradaufkommens im Verkehr, die Akzeptanz bei Anwohnenden und Verkehrsteilnehmenden sowie Nutzungspräferenzen von Lastenradfahrenden untersucht.
Der Lehrstuhl Logistische Systeme bildet gemeinsam mit der Abteilung Umweltpsychologie am Institut für Psychologie ein interdisziplinäres Team. Während auf logistischer Seite Verkehrsräume modelliert und simuliert werden, sind im Bereich der psychologischen Akzeptanzforschung eine qualitative Befragung von Sachverständigen (z.B. aus Lieferbranche, Planung, kommunalen Verwaltungen) und eine quantitative Befragung einer für Städte repräsentativen Stichprobe geplant.
Das Vorhaben zielt im Sinne des Nationalen Radverkehrsplans 2020 auf eine Verbesserung der Verkehrsqualität, eine Sicherung nachhaltiger Mobilität, eine breite Anwendbarkeit der Ergebnisse und die Generierung neuer Erkenntnisse. Es wird durch das Bundesministerium für Verkehr und digitale Infrastruktur (BMVI) aus Mitteln zur Umsetzung des Nationalen Radverkehrsplans 2020 gefördert.
Dem Projekt steht ein Projektbeirat zur Seite. Dieser besteht aus den folgenden Mitgliedern:
- Cargobike.jetzt
- Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
- DPD Deutschland GmbH
- PedalPower Schönstedt&Busack GbR
- United Parcel Service (UPS)
- Stadt Köln
- Zentrum für angewandte Psychologie, Umwelt- und Sozialforschung (ZEUS GmbH).
2024
Book chapter
Optimizing safety stock placement in large real-world automotive supply networks using the Guaranteed-service Model
Rolf, Benjamin; Lavassani, Kayvan; Lang, Sebastian; Reggelin, Tobias
In: Proceedings of the 57th Annual Hawaii International Conference on System Sciences , 2024 - Honolulu, HI : Department of IT Management, Shidler College of Business, University of Hawaii ; Bui, Tung X., S. 1669-1678 [Konferenz: 57th Hawaii International Conference on System Sciences, Honolulu, Hawaii, January 3-6, 2024]
Peer-reviewed journal article
Using Sentiment Analysis to Detect Disruptive Events in Supply Chains
Vishnuthilak, Kiran Katoor; Rolf, Benjamin; Reggelin, Tobias; Lang, Sebastian
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 58 (2024), Heft 19, insges. 6 S.
A transformer-based deep reinforcement learning approach for dynamic parallel machine scheduling problem with family setups
Li, Funing; Lang, Sebastian; Tian, Yuan; Hong, Bingyuan; Rolf, Benjamin; Noortwyck, Ruben; Schulz, Robert; Reggelin, Tobias
In: Journal of intelligent manufacturing - Dordrecht [u.a.] : Springer Science + Business Media B.V . - 2024, insges. 34 S. [Online first]
Resource-efficient Edge AI solution for predictive maintenance
Artiushenko, Viktor; Lang, Sebastian; Lerez, Christoph; Reggelin, Tobias; Hackert-Oschätzchen, Matthias
In: Procedia computer science - Amsterdam [u.a.] : Elsevier, Bd. 232 (2024), S. 348-357
A review on unsupervised learning algorithms and applications in supply chain management
Rolf, Benjamin; Beier, Alexander; Jackson, Ilya; Müller, Marcel; Reggelin, Tobias; Stuckenschmidt, Heiner; Lang, Sebastian
In: International journal of production research - London [u.a.] : Taylor & Francis . - 2024, insges. 51 S. [Online first]
2023
Essay
A scoping review on dynamic networks in supply chains
Rolf, Benjamin; Klementzki, Vanessa; Lang, Sebastian; Jackson, Ilya; Trojahn, Sebastian; Reggelin, Tobias
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 56 (2023), Heft 2, S. 203-214
Book chapter
Ereignisdiskrete Modellierung autonomer Transportfahrzeuge mittels Open-Source Software - Discrete-event modelling of autonomous transport vehicles using open-source software
Artiushenko, Viktor; Müller, Marcel; Reggelin, Tobias; Lang, Sebastian
In: Simulation in Produktion und Logistik 2023 / ASIM-Fachtagung Simulation in Produktion und Logistik , 2023 - Ilmenau : Universitätsverlag Ilmenau ; Bergmann, Sören *1979-*, S. 271-280 [Tagung: 20. ASIM Fachtagung Simulation in Produktion und Logistik, Ilmenau, 13-15. September 2023]
Introduction to the minitrack “Simulation modeling and digital twins for decision making in the age of Industry 4.0"
Reggelin, Tobias; Galka, Stefan; Strassburger, Steffen; Lang, Sebastian
In: Proceedings of the 56th Annual Hawaii International Conference on System Sciences , 2023 - Honolulu, HI : Department of IT Management, Shidler College of Business, University of Hawaii ; Bui, Tung X., S. 1436-1437 [Konferenz: The 56th Hawaii International Conference on System Sciences, 2023]
AI Engineering als interdisziplinäres Einführungsmodul zwischen Künstlicher Intelligenz und Ingenieurwesen
Lang, Sebastian; Siegert, Ingo; Artiushenko, Viktor; Schleiss, Johannes
In: Informatik 2023 - Berlin : Gesellschaft für Informatik e.V. ; Klein, Maike, S. 381-384 - (GI-Edition. Proceedings; volume P-337) [Tagung: Informatik 2023, Berlin, 26. - 29. September 2023]
Peer-reviewed journal article
A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
Li, Funing; Lang, Sebastian; Hong, Bingyuan; Reggelin, Tobias
In: Journal of intelligent manufacturing - Dordrecht [u.a.] : Springer Science + Business Media B.V . - 2023, insges. 34 S.
Dissertation
Methoden des bestärkenden Lernens für die Produktionsablaufplanung
Lang, Sebastian
In: [Heidelberg]: Springer Vieweg, Dissertation Otto-von-Guericke-Universität Magdeburg 2023, XXXIII, 286 Seiten, ISBN: 978-3-658-41750-5 [Literaturverzeichnis: Seite 267-286][Literaturverzeichnis: Seite 267-286]
2022
Book chapter
Introduction to the minitrack “Simulation modeling and digital twins for decision making in the age of Industry 4.0”
Reggelin, Tobias; Galka, Stefan; Ivanov, Dmitry; Lang, Sebastian
In: Proceedings of the 55th Annual Hawaii International Conference on System Sciences , 2022 - Honolulu, HI : Department of IT Management, Shidler College of Business, University of Hawaii at Manoa ; Bui, Tung X., S. 1954 [Konferenz: The 55th Hawaii International Conference on System Sciences, 2022]
Peer-reviewed journal article
A brief introduction to deploy Amazon Web Services for online discrete-event simulation
Hofmann, Wladimir; Lang, Sebastian; Reichardt, Paul; Reggelin, Tobias
In: Procedia computer science - Amsterdam [u.a.] : Elsevier, Bd. 200 (2022), S. 386-393 [Part of special issue: 3rd International Conference on Industry 4.0 and Smart Manufacturing]
A review on reinforcement learning algorithms and applications in supply chain management
Rolf, Benjamin; Jackson, Ilya; Müller, Marcel; Lang, Sebastian; Reggelin, Tobias; Ivanov, Dmitry
In: International journal of production research - London [u.a.] : Taylor & Francis, Bd. 60 (2022), insges. 30 S. [Published online: 03. Nov. 2022]
Using knowledge graphs and human-centric artificial intelligence for reconfigurable supply chains - a research framework
Rolf, Benjamin; Mebarki, Nasser; Lang, Sebastian; Reggelin, Tobias; Cardin, Olivier; Mouchère, Harold; Dolgui, Alexandre
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 55 (2022), Heft 10, S. 1693-1698 [Konferenz: 10th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2022, Nantes, France, 22-24 June 2022]
Integration of the A2C algorithm for production scheduling in a two-stage hybrid flow shop environment
Gerpott, Falk T.; Lang, Sebastian; Reggelin, Tobias; Zadek, Hartmut; Chaopaisarn, Poti; Ramingwong, Sakgasem
In: Procedia computer science - Amsterdam [u.a.] : Elsevier, Bd. 200 (2022), S. 585-594 [Part of special issue: 3rd International Conference on Industry 4.0 and Smart Manufacturing]
Article in conference proceedings
Developing a decision support system for integrated decision-making in purchasing and scheduling under lead time uncertainty
Rolf, Benjamin; Reggelin, Tobias; Lang, Sebastian; Galka, Stefan
In: Proceedings of the 55th Annual Hawaii International Conference on System Sciences , 2022 - Honolulu, HI : Department of IT Management, Shidler College of Business, University of Hawaii at Manoa ; Bui, Tung X., S. 1964-1973 [Konferenz: 55th Hawaii International Conference on System Sciences, HICSS55, online, 2022]
2021
Book chapter
Introduction to the minitrack on modeling and decision making in manufacturing and logistics in the age of industry 4.0
Reggelin, Tobias; Galka, Stefan; Lang, Sebastian; Ivanov, Dmitry
In: Hawaii International Conference on System Sciences 2021 , 2021 - Honolulu, HI : University of Hawai'i at Manoa, Hamilton Library, S. 1643-1644
Procedure model for the development and launch of intelligent assistance systems
Reichardt, Paul; Lang, Sebastian; Reggelin, Tobias
In: Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020) , 2020 - [Amsterdam u.a.] : Elsevier ; Longo, Francesco, Bd. 180 (2021), S. 968-977 [Konferenz: ISM 2020]
Simulationsmodell mit 3D-Animation zur schnellen Bewertung von Ablaufplänen in der Produktion - Simulation model with 3D animation for quick evaluation of production schedules
Rolf, Benjamin; Reggelin, Tobias; Lang, Sebastian; Müller, Marcel; Prehm, Johann
In: Simulation in Produktion und Logistik 2021 , 1. Auflage - Göttingen : Cuvillier Verlag ; Franke, Jörg *1964-*, S. 207-216 [Tagung: 19. ASIM-Fachtagung Simulation in Produktion und Logistik, Erlangen, 15. - 17. September 2021; Literaturangaben]
From logistics process models to automated integration testing - proof-of-concept using open-source simulation software
Reichardt, Paul; Hofmann, Wladimir; Reggelin, Tobias; Lang, Sebastian
In: IEEE Xplore digital library / Institute of Electrical and Electronics Engineers - New York, NY : IEEE . - 2021, insges. 11 S. [Konferenz: 2021 Winter Simulation Conference (WSC), Phoenix, AZ, 12-15. Dec. 2021]
Peer-reviewed journal article
Open-source discrete-event simulation software for applications in production and logistics - an alternative to commercial tools?
Lang, Sebastian; Reggelin, Tobias; Müller, Marcel; Nahhas, Abdulrahman
In: Procedia computer science - Amsterdam [u.a.] : Elsevier, Bd. 180 (2021), S. 978-987 [Part of special issue: Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020)]
NeuroEvolution of augmenting topologies for solving a two-stage hybrid flow shop scheduling problem - a comparison of different solution strategies
Lang, Sebastian; Reggelin, Tobias; Schmidt, Johann; Müller, Marcel; Nahhas, Abdulrahman
In: Expert systems with applications - Amsterdam [u.a.] : Elsevier Science - Vol. 172 (2021), article 114666, insgesamt 19 Seiten
Modeling production scheduling problems as reinforcement learning environments based on discrete-event simulation and OpenAI Gym
Lang, Sebastian; Kuetgens, Maximilian; Reichardt, Paul; Reggelin, Tobias
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 54 (2021), Heft 1, S. 793-798 [Part of special issue: 17th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2021: Budapest, Hungary, 7-9 June 2021]
2020
Book chapter
Comparison of deadlock handling strategies for different warehouse layouts with an AGVS
Müller, Marcel; Ulrich, Jan Hendrik; Reggelin, Tobias; Lang, Sebastian; Reyes-Rubiano, Lorena Silvana
In: IEEE Xplore digital library / Institute of Electrical and Electronics Engineers - New York, NY : IEEE . - 2020, S. 1300-1311 [Konferenz: 2020 Winter Simulation Conference (WSC), first virtual Winter Simulation Conference December 14-18, 2020.]
Integration of deep reinforcement learning and discrete-event simulation for real-time scheduling of a flexible job shop production
Lanzerath, Nico; Lang, Sebastian; Behrendt, Fabian; Reggelin, Tobias; Müller, Marcel
In: IEEE Xplore digital library / Institute of Electrical and Electronics Engineers - New York, NY : IEEE . - 2020, S. 3057-3068 [Konferenz: 2020 Winter Simulation Conference (WSC), first virtual Winter Simulation Conference December 14-18, 2020.]
Scheduling jobs in a two-stage hybrid flow shop with a simulation-based genetic algorithm and standard dispatching rules
Rolf, Benjamin; Reggelin, Tobias; Nahhas, Abdulrahman; Müller, Marcel; Lang, Sebastian
In: IEEE Xplore digital library / Institute of Electrical and Electronics Engineers - New York, NY : IEEE . - 2020, S. 1584-1595 [Konferenz: 2020 Winter Simulation Conference (WSC), first virtual Winter Simulation Conference December 14-18, 2020.]
Evolving neural networks to solve a two-stage hybrid flow shop scheduling problem with family setup times
Lang, Sebastian; Reggelin, Tobias; Behrendt, Fabian; Nahhas, Abdulrahman
In: Hawaii International Conference on System Sciences 2020 , 2020 - Honolulu, Hawaii : ScholarSpace, S. 1298-1307, 1 Online-Ressource (1,05 MB) [Konferenz: 53rd Hawaii International Conference on System Sciences 2020, Honolulu, Hawaii, 2020.01.06-10]
Transparency and training in manufacturing and logistics processes in times of industry 4.0 for Smes
Strubelt, Henning; Trojahn, Sebastian; Lang, Sebastian
In: IEEE Xplore digital library / Institute of Electrical and Electronics Engineers - New York, NY : IEEE . - 2019, S. 2013-2024 [Konferenz: 2019 Winter Simulation Conference, WSC, National Harbor, MD, USA, 8-11 December 2019]
Peer-reviewed journal article
Impact assessment model for the implementation of cargo bike transshipment points in urban districts
Assmann, Tom; Lang, Sebastian; Müller, Florian; Schenk, Michael
In: Sustainability - Basel : MDPI - Volume 12 (2020), issue 10, article 4082, 19 Seiten
Mesoscopic discrete-rate-based simulation models for production and logistics planning
Reggelin, Tobias; Lang, Sebastian; Schauf, Christian
In: Journal of simulation - Abingdon : Taylor & Francis Group - Vol. 14 (2020), 4, insgesamt 10 Seiten
Assigning dispatching rules using a genetic algorithm to solve a hybrid flow shop scheduling problem
Rolf, Benjamin; Reggelin, Tobias; Nahhas, Abdulrahman; Lang, Sebastian; Müller, Marcel
In: Procedia manufacturing - Amsterdam [u.a.] : Elsevier, Bd. 42 (2020), S. 442-449 [Konferenz: International conference on Industry 4.0 and Smart Manufacturing (ISM 2019)]
2019
Peer-reviewed journal article
Towards learning- and knowledge-based methods of artificial intelligence for short-term operative planning tasks in production and logistics - research idea and framework
Lang, Sebastian; Schenk, Michael; Reggelin, Tobias
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 52 (2019), Heft 13, S. 2716-2721 [Part of special issue: 9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019: Berlin, Germany, 2830 August 2019]
Integration of LiFi technology in an Industry 4.0 learning factory
Mukku, Vasu Dev; Lang, Sebastian; Reggelin, Tobias
In: Procedia manufacturing - Amsterdam [u.a.] : Elsevier, Bd. 31 (2019), S. 232-238 [Part of special issue: Research. Experience. Education. 9th Conference on Learning Factories 2019 (CLF 2019), Braunschweig, Germany]
2018
Essay
Scheduling approach for the simulation of a sustainable resource supply chain
Strubelt, Henning; Trojahn, Sebastian; Lang, Sebastian; Nahhas, Abdulrahman
In: Logistics - Basel : MDPI AG, Bd. 2 (2018), Heft 3, S. 1-11
Book chapter
Toward adaptive manufacturing - scheduling problems in the context of Industry 4.0
Nahhas, Abdulrahman; Lang, Sebastian; Bosse, Sascha; Turowski, Klaus
In: 2018 Sixth International Conference on Enterprise Systems , 2018 - Piscataway, NJ : IEEE ; Papadopoulos, George A. *1960-*, S. 108-115 [Konferenz: 2018 Sixth International Conference on Enterprise Systems (ES), Limassol, Cyprus, 1-2 October 2018]
Towards a modular, decentralized and digital industry 4.0 learning factory
Lang, Sebastian; Regelin, Tobias; Motasem, Jobran; Hofmann, Wladimir
In: 2018 Sixth International Conference on Enterprise Systems , 2018 - Piscataway, NJ : IEEE, S. 123-128 [Konferenz: 2018 Sixth International Conference on Enterprise Systems (ES), Limassol, Cyprus, 1-2 October 2018]
Discussing the application potentials of Microsoft HoloLens-TM in production and logistics - a literature review and case study
Lang, Sebastian; Kota, Mohammed S. S. D.; Weigert, David
In: The 4th International Conference of the Virtual and Augmented Reality in Education (VARE 2018) - Rende, Italy, S. 188-197 [Konferenz: VARE 2018]
Peer-reviewed journal article
Simulation and virtual commissioning of modules for a plug-and-play conveying system
Hofmann, Wladimir; Ulrich, Jan Hendrik; Lang, Sebastian; Reggelin, Tobias; Tolujew, Juri
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 51 (2018), Heft 11, S. 649-654
Applying methods of artificial intelligence for optimization in production and logistics
Lang, Sebastian
In: Research and technology - step into the future - Riga : Transport and Telecommunication Institute, Bd. 13 (2018), Heft 2, S. 21-29 [Special issue: PhD seminar Sci-Bi: Digitalization in Logistics and Transport, 16 October 2018, Riga]
Article in conference proceedings
Applying methods of artificial intelligence for optimization in production and logistics
Lang, Sebastian
In: 11th International Doctoral Students Workshop on Logistics - June 19, 2018, Magdeburg , 2018 - Magdeburg : Institut für Logistik und Materialflusstechnik an der Otto-von-Guericke-Universität Magdeburg, S. 97-102 [Konferenz: 11th International Doctoral Students Workshop on Logistics, Magdeburg, 19.06.2018]
2017
Book chapter
Forecast models and hierarchical combined discrete-rate/discrete-event simulation models for parcel service networks
Lang, Sebastian; Reggelin, Tobias; Manner-Romberg, Horst
In: The 19th International Conference on Harbor, Maritime and Multimodal Logistics Modelling and Simulation (HMS 2017) - Genova : DIME Università, S. 111-118 [Konferenz: HMS 2017]
Application of discrete-rate based mesoscopic simulation models for production and logistics planning
Reggelin, Tobias; Schauf, Christian; Lang, Sebastian; Weigert, David
In: The 19th International Conference on Harbor, Maritime and Multimodal Logistics Modelling and Simulation (HMS 2017) - Genova : DIME Università, S. 141-147 [Konferenz: HMS 2017]
Simulation-based training modules for independent training of employees in the automotive industry
Friedrichs, Alexander; Reggelin, Tobias; Lang, Sebastian; Wunder, Toralf
In: The 19th International Conference on Harbor, Maritime and Multimodal Logistics Modelling and Simulation (HMS 2017) - Genova : DIME Università, S. 125-130 [Konferenz: HMS 2017]
Mesoskopische Simulationsmodelle in der Produktions- und Logistikplanung
Reggelin, Tobias; Lang, Sebastian; Weigert, David; Schauf, Christian
In: Simulation in Produktion und Logistik 2017 / Fachtagung Simulation in Produktion und Logistik , 2017 - Kassel : Kassel University Press, S. 199-208
Comparison of a microscopic discrete-event and a mesoscopic discrete-rate simulation model for planning a production line
Gleye, Florian; Reggelin, Tobias; Lang, Sebastian
In: The 29th European Modeling and Simulation Symposium (EMSS 2017) - Genova : DIME Universitá, S. 444-448 [Konferenz: EMSS 2017]
Peer-reviewed journal article
Mesoscopic simulation models for logistics planning tasks in the automotive industry
Lang, Sebastian; Reggeling, Tobias; Wunder, Toralf
In: Procedia engineering - Amsterdam [u.a.] : Elsevier, Bd. 178 (2017), S. 298-307 [Konferenz: RelStat-2016, 19.-22.10.2016, Riga, Latvia]
Integrating virtual commissioning based on high level emulation into logistics education
Hofmann, Wladimir; Langer, Sebastian; Lang, Sebastian; Reggelin, Tobias
In: Procedia engineering - Amsterdam [u.a.] : Elsevier, Bd. 178 (2017), S. 24-32 [Konferenz: RelStat-2016, 19.-22.10.2016, Riga, Latvia]
2016
Book chapter
Integrating virtual commissioning based on high level emulation into logistics education
Hofmann, Wladimir; Langer, Sebastian; Lang, Sebastian; Reggelin, Tobias
In: The 16th International Conference Reliability and Statistics in Transportation and Communication, (RelStat'16) - Riga : Transport und Telecommunication Institute . - 2016, S. 486-494
Emulation als Teil eines Materialflusslabors
Langer, Sebastian; Hofmann, Wladimir; Lang, Sebastian
In: Logistik neu denken und gestalten - 21. Magdeburger Logistiktage : Tagungsband / Magdeburger Logistiktage "Logistik Neu Denken und Gestalten" , 2016 - Magdeburg : Fraunhofer-Institut für Fabrikbetrieb und -automatisierung IFF, S. 183-193 [Kongress: 21. Magdeburger Logistiktage "Logistik neu denken und gestalten", Magdeburg, 22. - 23. Juni, 2016]
Emulation as part of an integrated logistics learning environment
Langer, Sebastian; Hofmann, Wladimir; Lang, Sebastian; Reggelin, Tobias; Weigert, David
In: The 28th European Modeling & Simulation Symposium, EMSS 2016 - Genoa : DIPTEM, S. 134-140 [Kongress: 28th European Modeling & Simulation Symposium, EMSS 2016, Cyprus, 26-28 September, 2016]
Mesoscopic simulation for automotive industry applications
Lang, Sebastian; Reggelin, Tobias; Wunder, Toralf
In: The 16th International Conference Reliability and Statistics in Transportation and Communication, (RelStat'16) - Riga : Transport und Telecommunication Institute . - 2016, S. 582-590
2015
Book chapter
Hierarchical mesoscopic simulation models of parcel service provider networks
Erichsen, Björn; Reggelin, Tobias; Lang, Sebastian; Manner-Romberg, Horst
In: The 17th International Conference on Harbor, Maritime and Multimodal Logistics Modelling and Simulation - DIME Università di Genova . - 2015, S. 73-78
- Einführung in das AI Engineering ( Link zur LV im LSF )
- Einführung in das AI Engineering - Übung ( Link zur LV im LSF )
- Fundamentals of Artificial Intelligence in Production and Logistics ( Link zur LV im LSF )
- Fundamentals of Artificial Intelligence in Production and Logistics ( Link zur LV im LSF )
- Industrielle KI-Systeme ( Link zur LV im LSF )
- Projekt Machine Learning Programmierung ( Link zur LV im LSF )