TY - CHAP A1 - Rolf, Benjamin A1 - Reggelin, Tobias A1 - Lang, Sebastian A1 - Galka, Stefan T1 - Developing a Decision Support System for Integrated Decision-Making in Purchasing and Scheduling under Lead Time Uncertainty T2 - Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS55): January 3-7, 2022, Maui, Hawaii, USA N2 - Decision-making in supply chain management is complex because of the relations between planning tasks from different stages and planning levels. Uncertainties such as unpredictable supplier lead times and supply chain disruptions further complicate decision-making. Considering the case study of a company in printed circuit board assembly, a three-level concept is proposed that includes a decision support system. The global single-source supply network is characterized by highly variable lead times. Hence, the company maintains high inventory levels to prevent running out of stock. The decision support system considers the purchasing and scheduling decision problems in an integrated way. The prototypical implementation of the purchasing algorithm uses a genetic algorithm that recommends reorder days and order quantities using a simulation model. In addition, it evaluates the risks of the recommended solution by calculating the probability of stockouts for each order cycle. KW - decision support system KW - simulation KW - supply chain optimization, KW - purchasing KW - cyber-physical system KW - Industry 4.0 Y1 - 2022 U6 - https://doi.org/10.24251/HICSS.2022.247 VL - 2022 SP - 1964 EP - 1973 ER - TY - JOUR A1 - Klenk, Eva Marianne A1 - Galka, Stefan T1 - Analysis of real-time tour building and scheduling strategies for in-plant milk-run systems with volatile transportation demand JF - IFAC - PapersOnLine N2 - In modern manufacturing systems, milk run (MR) systems represent route-based, cyclic material-handling systems that are used widely and enable frequent deliveries of containerized parts in small lot sizes from a central storage area to multiple points of use on the factory floor. Usually, deliveries take place at predetermined, constant time intervals. As in real-world MR systems, the number of containers to deliver in each interval varies in the short term, peaks in the number of deliveries may lead to capacity bottlenecks and late deliveries. In this paper, we develop three alternative strategies to determine starting times of MR cycles in real-time based on the current number of delivery orders in the system aiming to better handle variations in the number of orders. We evaluate the three strategies for different system load scenarios with respect to delivery service levels, order lead times, systems utilization and necessary number of MR trains using a discrete-event simulation model. KW - Control algorithms KW - Logistics KW - Material handling KW - Milk-run systems KW - Production systems KW - Real-time decision making KW - Transportation control Y1 - 2019 U6 - https://doi.org/10.1016/j.ifacol.2019.11.517 VL - 52 IS - 13 SP - 2110 EP - 2115 PB - Elsevier ER - TY - CHAP A1 - Schuhegger, Lukas A1 - Armbruster, Thomas A1 - Galka, Stefan T1 - Factory Data Model for Planning Variant Sequences, Expansion Stages and Reconfigurations T2 - IFAC-PapersOnLine N2 - A factory has to adapt to a future production program and increasing volumes. The planning of new factories must therefore already take expansion stages and reconfigurations into account. This leads to an increase in the complexity of planning, as different variants have to be planned and put into a chronologically reasonable and cost-optimized sequence. A factory data model that covers expansion stages manages the planning data amount and reduces complexity. Based on existing models from the literature, a factory data model was developed and modeled in the Unified Modeling Language standard. The factory data model shows which classes are interdependent and how planning results are stored reusable for other variants. An example is used to explain the developed factory data model and highlighting its advantages. The aim is to enable factory planners to document variant sequences and expansion stages in a comprehensible way, which supports the interdisciplinarity of factory planning projects. Y1 - 2023 U6 - https://doi.org/10.1016/j.ifacol.2023.10.1573 VL - 56 IS - 2 SP - 227 EP - 232 PB - IFAC / Elsevier ER - TY - JOUR A1 - Galka, Stefan A1 - Wappler, Mona T1 - Integration of cash flow management and further aspects of the supply chain management in production system design JF - IFAC-PapersOnLine N2 - One major goal of production system design is to decide on space requirements in the plant. In this phase, detailed information about the supply chain network (e.g. which suppliers deliver which parts) is often unavailable. Nevertheless, typical decisions in supply chain management, like the definition of replenishment processes and quantities or make-or-buy decisions, impact space requirements and the capital investment in raw materials. Therefore, it should be considered in factory and production planning. This research article proposes a simulation approach for a production simulation in which raw material replenishment is integrated to evaluate the capital investment and space requirements for raw materials. Y1 - 2023 U6 - https://doi.org/10.1016/j.ifacol.2023.10.1687 VL - 56 IS - 2 SP - 947 EP - 952 PB - IFAC / Elsevier ER -