CourseWinter Term 2025/26
Computer-Simulation: Ereignisdiskrete & Hybride Systeme
Hochschulkurs zu Computer-Simulation an der FH OÖ: Stochastische Modellierung, Discrete-Event-Engines in C#, DGL-Löser und statistische Validierung.
CourseSummer Term 2025
Internet der Dinge (IoT): Embedded C# & ThingsBoard
Praxisorientierter Hochschulkurs zum Internet der Dinge (IoT) mit ESP32-Firmware in C# (.NET nanoFramework), MQTT-Telemetrie und ThingsBoard Cloud.
PresentationSep 25, 2026
Vom Web-Pionier zum Informatik-Professor: 25 Jahre im Code
Persönliche Keynote von Dr. Georg Hackenberg: 25 Jahre im Code zwischen autodidaktischen Web-Ursprüngen, Spitzenforschung, Industrie-IoT-Leadership und offener Hochschullehre.

PublicationJan 1, 2025
On modeling, discrete-event simulation, and optimization of spine layouts
Today, discrete-event simulation (DES) has proven to be an essential tool for designing complex high-performance and cost-effective manufacturing systems. However, a significant challenge still lies in modeling specialized system layouts such as the spine layout, which is characterized by a central aisle flanked by corridors with workstations and served by an overhead automated material handling system. While the spine layout has demonstrated to be suitable in industries with complex operational requirements, current DES tools still lack dedicated modeling constructs for this type of layout and its characteristic properties, making the modeling process time-consuming and error-prone. To overcome the current situation, we develop a basic formalism that captures essential properties of spine layouts and defines their inherent discrete-event simulation semantics. Furthermore, we elaborate on the layout …
Project
SpineML: Factory Layout & Job Shop Optimization
A Python toolkit designed to optimize factory layout planning (FLP) and job shop scheduling (JSS) through advanced layout modeling and simulation.
PostSep 18, 2026
Procedural Graphs: Zuverlässige KI-Prozessautomatisierung
Warum ĂĽber 80 % agentischer Pilotprojekte scheitern und wie Googles Procedural Graphs Standard Operating Procedures in selbstlernende Graphen ĂĽberfĂĽhren.