Modelling and Simulation of Production Systems
FSI-GMV-KAcad. year: 2020/2021
The aim of the course is to provide students with the practical knowledge in the field of modern methods for the simulation and modelling of production systems in kontext of Industry 4.0. It focuses primarily on technological processes and manufacturing systems and applies the principles of continuous and discrete simulation for their modelling. The application of simulation methods to designing and controlling discrete systems and processes is analysed, in the field of a strategic planning, operational control and ergonomics.
Learning outcomes of the course unit
Students will acquire the knowledge necessary for a deeper understanding of the principles and methods used in simulation. They will learn to apply this knowledge in the creation of simulation models in the field of technical, especially production systems.
Students should be able to prepare a simulation model of production, to process and evaluate various alternatives.
The student should be able to:
- knowledge of basic principles of production systems and machines and their functionality
- basic knowledge of mathematics in the field of differential equations, matrix operations and statistics
- Basic PC skills including various types of data processing software (Excel, Matlab, etc.).
Recommended optional programme components
Recommended or required reading
Averill M. Law, W. David Kelton: Simulation Modeling and Analysis
Neuschl Štefan a kol.: Modelovanie a simulácia, ALFA, 1989
Kuneš Jozef a kol.: Základy modelování ,SNTL , 1989
A. Alan B. Pritsker, Claude D. Pegden: Introduction to Simulation and SLAM II
Zítek Pavel: : Simulace dynamických systémů , SNTL, 1989
Jerry Banks, Discrete-Event System Simulation
Planned learning activities and teaching methods
The course is taught through lectures explaining the basic principles and theory of the discipline. Teaching is suplemented by practical laboratory work.
According to the possibility of teaching can be organized lectures for students by practitioners and excursions to companies focused on activities related to the course content.
Assesment methods and criteria linked to learning outcomes
Course-unit credit is conditional on the following:
1. Attendance at exercises (except documented excusable absence)
2. Fulfillment of the conditions of continuous control (preparation for exercise, activity during exercise); these requirements will be specified at the beginning of the semester in practice.
3. Elaboration and demonstration of assigned tasks
The exam verifies the acquired knowledge. The exam is combined. In the written part verifies the ability of the student to apply the acquired knowledge and methods in the test and in the oral part if necessary verifies the knowledge of theoretical foundations.
Language of instruction
The course aims to provide students with skills in computer simulation systems, especially manufacturing systems. Students will acquire skills in the preparation of simulation models, both continuous and discrete. Furthermore, they learn about methods of linking continuous and discrete modeling.
Specification of controlled education, way of implementation and compensation for absences
Attendance at obligatory lessons is checked and only substantial reasons of absence are accepted. Missed lessons can be substituted for via solution of extra exercises.
Classification of course in study plans
- Programme N-VSR-K Master's, 1. year of study, summer semester, 4 credits, compulsory-optional
Type of course unit
Guided consultation in combined form of studies
17 hours, compulsory
Teacher / Lecturer
1. Introduction to modeling and simulation of systems. Systems analysis and classification. Basic concepts of systems theory.
2. Mathematical basics of modeling and simulation.
3.-4. Classification of models. Basic methods of continuous systems modeling.
5.-6. Classification of models. Basic methods of discrete systems modeling.
7. Event-driven simulation method, compilation and use of event calendar
8.-9. Modeling of stochastic systems, use of statistical methods, generation of random variables.
10. Traceability of real technical systems of production systems in discrete simulation.
11. Simulation languages, overview of basic tools for model and experiment description.
12. Evaluation and visualization of simulation results.
13. Interconnection of real and simulated systems, data exchange, model verification.
35 hours, optionally
Teacher / Lecturer
1.-2. Simulation languages, overview of basic tools for model and experiment description. Basic principles of simulation systems implementation.
3. Continuous modeling - model creation and work with it.
4.-6.Discrete modeling, event-driven modeling, model preparation and creation.
7.-8. Interconnection of continuous and discrete modeling.
9. Methods modeling of production systems in the typical condition of use of sensor data; ways of linking the model to off-line and on-line data in the context of Industry 4.0; Using the model for design and planning of production system.
10.-13. Individual project work