Simulation of production systems
Participants in this master course will develop skills in discrete event simulation to meet the needs of today's manufacturing industry.
Through use of discrete event simulation you will learn to support improvements of industrial processes involving complex changes. The course focuses on how to build, analyse and communicate the results of a simulation study. You will acquire knowledge through theoretical understanding, practical exercises and workshops. Based on a real case, the course will guide you to be able to improve production and logistics flow with discrete event simulation.
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- Introduction to discrete event simulation in production systems
- Discrete event simulation in research and manufacturing practice
- Principles for simulation and system modelling
- Basic concepts for data collection and analysis
- Establish the relationship between the system elements
- Simulation project: From problem to model
- Impact of modelling accuracy: Validation and verification
- Techniques for simulation and system modelling
- Simulation modelling strategies
- Analysis of different scenarios
- Communication of simulation results
You will learn to
- Develop a simulation model based on a real-world problem by use of conceptual modelling.
- Develop simulation models for production systems by using a systems perspective, applying simulation concepts and understanding the relation between system elements.
- Build simulation models for a production system where you apply data collection, analysis, detailed model design and modelling strategies
- Experiment with variation and changes in simulation models by analysing scenarios and documenting activities and finally, applying this knowledge on a case study.
40 credits in Engineering/Technology and at least two years’ experience in full-time employment in a relevant area within industry. In addition English course A/English course 6 is required.
If you do not have the formal academic qualifications required, you can have your eligibility evaluated based on knowledge acquired in other ways, such as work experience, other studies etc.