Digital Factory Simulation & Production Engineering

Master-level university course on Digital Factory Simulation and production engineering with discrete-event modeling and 3D layouts in JaamSim.

#simulation#factory-layout#industrial-informatics#teaching
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In modern manufacturing, building physical prototypes to test layout variations is costly and slow. Discrete Event Simulation (DES) enables engineers to construct high-fidelity digital factory twins, optimize throughput, and validate complex material flow logistics before purchasing machinery.

Target Audience

Master's students in Industrial Informatics, Mechatronics, and Software Engineering, as well as production automation practitioners.

Course Prerequisites

  • Fundamental understanding of manufacturing processes and industrial workflows
  • Basic principles of probability, distributions, and queuing theory
  • Introductory programming or scripting experience

Learning Goals

  • Discrete Event Simulation: Formulate event-driven time advance models and stochastic process queues.
  • Digital Twin Modeling: Build parametric 3D factory cells and conveyor routing in JaamSim.
  • Bottleneck & Flow Analysis: Diagnose machine starvation, buffer blocking, and optimize overall equipment effectiveness.
  • Statistical Validation: Design simulation experiments, run replications, and compute confidence intervals.

Course Syllabus

  1. Foundations of Discrete Event Simulation: Foundations of discrete-event simulation (DES) in digital factory planning: system state transitions, future event lists, and next-event time advance.
  2. JaamSim Essentials & Layout Construction: Building interactive 3D factory layouts in JaamSim: entity generators, queues, servers, conveyors, stochastic arrival distributions, and CAD imports.
  3. Advanced Flow Control & Assembly Logic: Modeling complex manufacturing material flows: assembly and disassembly stations, batching, conditional attribute routing, and resource pools.
  4. Maintenance, Failures & Downtime: Simulating stochastic machine breakdowns and maintenance schedules using Weibull/exponential MTBF and MTTR distributions, shift calendars, and buffers.
  5. Simulation Analytics & Bottleneck Optimization: Statistical output analysis for digital factory models: warm-up truncation, confidence intervals, bottleneck detection, and throughput optimization.

Course Modules

Structured learning units covering theoretical foundations, practical implementations, and industry tooling.

Module 01

Foundations of Discrete Event Simulation

Foundations of discrete-event simulation (DES) in digital factory planning: system state transitions, future event lists, and next-event time advance.

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Module 02

JaamSim Essentials & Layout Construction

Building interactive 3D factory layouts in JaamSim: entity generators, queues, servers, conveyors, stochastic arrival distributions, and CAD imports.

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Module 03

Advanced Flow Control & Assembly Logic

Modeling complex manufacturing material flows: assembly and disassembly stations, batching, conditional attribute routing, and resource pools.

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Module 04

Maintenance, Failures & Downtime

Simulating stochastic machine breakdowns and maintenance schedules using Weibull/exponential MTBF and MTTR distributions, shift calendars, and buffers.

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Module 05

Simulation Analytics & Bottleneck Optimization

Statistical output analysis for digital factory models: warm-up truncation, confidence intervals, bottleneck detection, and throughput optimization.

Read More