TY - CHAP A1 - Scholz, Michael A1 - Serno, Mario A1 - Franke, Jörg A1 - Schuderer, Peter T1 - A Hybrid Transport Concept for the Material Supply of a Modular Manufacturing Environment T2 - Procedia Manufacturing N2 - Today's research projects propose a modular manufacturing environment for automotive production sites, which adapt itself autonomously and makes manufacturing decisions without the need of human interaction. Tugger trains are an energy-efficient possibility to handle intralogistics material supply due to the bundling of transport volumes but reaches its limits in the proposed automotive manufacturing environments. The spatial nearness of the production units and the necessity of a high-frequented and small-scaled supply lead to the application of small-scaled autonomous transport entities. The main disadvantage of this technology in turn is a higher intralogistics traffic. Therefore, the concluded concept of this paper connects the advantages of both technologies. UR - https://doi.org/10.1016/j.promfg.2017.07.275 KW - Tugger train KW - Automated Guided Vehicle KW - Hybrid system KW - Material Supply KW - Modular Manufacturing Environment Y1 - 2017 UR - https://doi.org/10.1016/j.promfg.2017.07.275 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-23515 SN - 2351-9789 VL - 2017 IS - 11 SP - 1448 EP - 1453 PB - Elsevier CY - Amsterdam ER - TY - RPRT A1 - Eden, Wolfgang A1 - Schuderer, Peter A1 - Donhauser, Toni A1 - Franke, Jörg T1 - Reduzierung des Energieverbrauchs und der CO2-Emissionen sowie Steigerung der Ressourceneffizienz durch eine zustandsorientierte Steuerung der Produktionsabläufe in Kalksandsteinwerken - betriebsbegleitende Simulation unter Einbindung von Echtzeitdaten KW - Kalksandsteinindustrie KW - Ressourceneffizienz Y1 - 2020 PB - Forschungsvereinigung Kalk-Sand e.V. CY - Hannover ER - TY - CHAP A1 - Zwingel, Maximilian A1 - Blank, Andreas A1 - Schuderer, Peter A1 - Franke, Jörg ED - Herberger, David ED - Hübner, Marco T1 - A Hybrid Metric for Navigation of Autonomous Intralogistics Vehicles in Mixed Indoor and Outdoor Operation T2 - Proceedings of the Conference on Production Systems and Logistics: CPSL 2022 N2 - While autonomous guided vehicle systems are increasingly used in homogeneous and structured environments, their use in complex and variable scenarios is usually limited. Established algorithms for the navigation of systems use static maps with deterministic metrics, which can only achieve optimal results in clearly defined environments. In dynamic and extensive deployment scenarios, which are also dependent on a large number of influencing parameters, autonomous intralogistics systems cannot yet be deployed dynamically. One example here is mixed transport between buildings under changing weather conditions. As a solution for dynamic navigation, we propose a hybrid metric in combination with topological maps and cyclic environmental sensing. Based on a quantification of influencing factors on each intralogistics entity, an optimal and dynamic navigation of every system can be performed at any time. The individual components are implemented in the context of an autonomous tow truck system and evaluated in different application scenarios. The results show significant added value in use cases with sudden weather changes and complex route networks. UR - https://doi.org/10.15488/12123 KW - Autonomous Tow Truck Systems KW - Topological Maps KW - Hybrid Metric Y1 - 2022 UR - https://doi.org/10.15488/12123 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-31219 SN - 2701-6277 SP - 785 EP - 794 PB - publish-ing CY - Hannover ER - TY - CHAP A1 - Schlosser, Alexander A1 - Schuderer, Peter A1 - Franke, Jörg ED - Kohl, Holger ED - Seliger, Günther ED - Dietrich, Franz ED - Vien, Ha Thuc T1 - Sustainability Assessment and Optimization in Construction Site: A Simulation-Based Approach T2 - Decarbonizing Value Chains: Proceedings of the 20th Global Conference on Sustainable Manufacturing (GCSM 2024), October 9–11, 2024, Ho Chi Minh City, Vietnam N2 - The construction industry is currently facing significant challenges. In order to address these challenges, the REMUS simulation model library for the construction industry is being developed. To this end, the physical modules are divided into stationary and mobile modules, as well as information objects. To create the simulation model and conduct the simulation experiment, a requirements cluster with the most important parameters of construction sites is created. The elements of sustainability—environmental, economy, and social aspects—are employed to assess the simulation results and to optimize the model. To this end, corresponding KPIs, methods, and procedures are delineated, which are documented during the various simulation experiments and evaluated subsequently. The equipment and environment exert an influence on the “economy”. This is reflected in the costs associated with the model components and their operation. The area of “environmental” is represented by the consumption of input materials. Alternative consumption and recovery concepts are implemented and compared here. The “social” aspect is represented by the human-machine collaboration. As part of the simulation experiments, the recorded variables are continuously adapted and refined. This process enables the simulation to improve the sustainability of the construction site environment. UR - https://doi.org/10.1007/978-3-031-93891-7_10 Y1 - 2025 UR - https://doi.org/10.1007/978-3-031-93891-7_10 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62843 SN - 978-3-031-93891-7 SP - 82 EP - 90 PB - Springer CY - Cham ER - TY - CHAP A1 - Schlosser, Alexander A1 - Barth, Martin A1 - Schuderer, Peter A1 - Franke, Jörg ED - Lam, H. ED - Azar, E. ED - Batur, D. ED - Gao, S. ED - Xie, W. ED - Hunter, R. ED - Rossetti, M. D. T1 - Optimizing the Automation in Construction Site Logistics: Problems and Propsed Modell Library for Materials Flow Simulation T2 - 2024 Winter Simulation Conference (WSC) UR - https://doi.org/10.1109/WSC63780.2024.10838777 Y1 - 2025 UR - https://doi.org/10.1109/WSC63780.2024.10838777 SN - 979-8-3315-3420-2 SP - 2393 EP - 2404 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schrage, Tobias A1 - Barth, Martin A1 - Schuderer, Peter A1 - Franke, Jörg ED - Bergman, Sören ED - Feldkamp, Niclas ED - Souren, Rainer ED - Straßburger, Steffen T1 - Entwicklung und Realisierung einer Modellbibliothek für ein Entscheidungsunterstützungssystem in der Kalksandsteinproduktion T2 - Simulation in Produktion und Logistik 2023 T2 - Development and Realisation of a Model Library for a Decision Support System in Calcium Silicate Brick Production UR - https://doi.org/10.22032/dbt.57787 KW - Entscheidungsunterstützungssystem KW - Kalksandstein KW - Modellbibliothek KW - model library KW - decision support system KW - calcium silicate brick Y1 - 2023 UR - https://doi.org/10.22032/dbt.57787 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-49979 SN - 978-3-86360-276-5 SP - 61 EP - 70 PB - Universitätsverlag Ilmenau CY - Ilmenau ER - TY - CHAP A1 - Schobert, Marvin A1 - Gmeiner, Christian A1 - Franke, Jörg A1 - Schuderer, Peter ED - Rank, Sebastian ED - Kühn, Mathias ED - Schmidt, Thorsten T1 - BPMN2.0 for the formal specification of discrete event simulation models T2 - Simulation in Produktion und Logistik 2025 N2 - Discrete Event Simulation (DES) is essential for planning in logistics, material flow, and production but remains time- and knowledge-intensive due to fragmented modelling practices and tool-specific requirements, as noted in VDI 3633 and VDI 4465. This paper proposes addressing these challenges by transferring concepts from Business Process Management, leveraging its formal modelling languages and validation frameworks. A style guide based on the Business Process Model and Notation 2.0 (BPMN) is introduced, structured around the principles of correctness, completeness, consistency, and clarity to support both communication and simulation. These principles enable reusable, verifiable process models suitable for execution in different DES tools, which serves as a step towards automated experimentation and verification. Through a first-ever evaluation of state of the art approaches against those principles, this work contributes to the ongoing definition of a semi-formal BPMN modelling layer developed in the ASIM SPL working group for formal methods in procedural models. T2 - BPMN2.0 für die formale Spezifikation von Modellen für die ereignisdiskrete Simulation UR - https://doi.org/10.25368/2025.285 Y1 - 2025 UR - https://doi.org/10.25368/2025.285 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62911 SN - 978-3-86780-806-4 SN - 978-3-86780-809-5 VL - 2025 SP - 52-1 EP - 52-10 PB - Technische Universität Dresden CY - Dresden ER - TY - CHAP A1 - Schrage, Tobias A1 - Schuderer, Peter A1 - Barth, Martin A1 - Franke, Jörg ED - Rank, Sebastian ED - Kühn, Mathias ED - Schmidt, Thorsten T1 - Konzeptionierung und Integration eines KI-basierten Autoklavenmodells in ein simulationsbasiertes Entscheidungsunterstützungssystem in der Kalksandsteinproduktion T2 - Simulation in Produktion und Logistik 2025 N2 - The calcium silicate brick (CSB) industry faces increasing pressure to improve the efficiency and sustainability of its production processes, especially due to the high energy consumption and CO₂ emissions associated with autoclaving. To support operational and strategic decision-making, a simulation-based decision support system (DSS) has been developed, utilizing a modular material flow simulation framework. However, the energy-intensive steam curing process in autoclaves remains insufficiently represented in existing simulation models. This paper presents a methodological approach for integrating an AI-based optimization agent for autoclave systems into the existing DSS used in CSB production. A review of current techniques for coupling AI assistance systems with discrete event simulation in production and logistics, within the building materials sector, provides the foundation. Building on this, the autoclaving process is modeled using a hybrid approach, combining thermodynamic domain knowledge with machine learning methods. This contribution highlights how the combination of simulation-based production planning and intelligent process modelling can drive digital transformation in energy-intensive industries. T2 - Conceptual design and integration of an AI-based autoclave model into a simulation-based decision support system in sand-lime brick production UR - https://doi.org/10.25368/2025.288 Y1 - 2025 UR - https://doi.org/10.25368/2025.288 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62862 SN - 978-3-86780-809-5 SN - 978-3-86780-806-4 SP - 55-1 EP - 55-10 PB - Technische Universität Dresden CY - Dresden ER -