Course detail
Modelling and Simulation of Production Systems
FSI-GMVAcad. 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.
Language of instruction
Czech
Number of ECTS credits
4
Mode of study
Not applicable.
Guarantor
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.
Students should be able to prepare a simulation model of production, to process and evaluate various alternatives.
Prerequisites
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.).
- 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.).
Co-requisites
Not applicable.
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.
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
Examination:
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.
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
Examination:
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.
Course curriculum
Not applicable.
Work placements
Not applicable.
Aims
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.
Recommended optional programme components
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
BANKS, Jerry. Discrete-event system simulation. 5th ed. Upper Saddle River: Prentice Hall, c2010. ISBN 978-013-6062-127.
(EN)
KUBÍČEK, Milan, Miroslava DUBCOVÁ a Drahoslava JANOVSKÁ. Numerické metody a algoritmy. 2. oprav. vyd. Praha: Vydavatelství VŠCHT Praha, 2005. ISBN 978-807-0805-589. (CS)
RÁBOVÁ, Zdena. Modelování a simulace. 3., přeprac. vyd. Brno: VUT, 1992. ISBN 80-214-0480-9. (CS)
ZÍTEK, Pavel. Matematické a simulační modely. Praha: Vydavatelství ČVUT, 2001. ISBN 80-010-2300-1. (CS)
ZÍTEK, Pavel. Simulace dynamických systémů. Praha: SNTL, 1990. ISBN 80-030-0330-X. (CS)
KUBÍČEK, Milan, Miroslava DUBCOVÁ a Drahoslava JANOVSKÁ. Numerické metody a algoritmy. 2. oprav. vyd. Praha: Vydavatelství VŠCHT Praha, 2005. ISBN 978-807-0805-589. (CS)
RÁBOVÁ, Zdena. Modelování a simulace. 3., přeprac. vyd. Brno: VUT, 1992. ISBN 80-214-0480-9. (CS)
ZÍTEK, Pavel. Matematické a simulační modely. Praha: Vydavatelství ČVUT, 2001. ISBN 80-010-2300-1. (CS)
ZÍTEK, Pavel. Simulace dynamických systémů. Praha: SNTL, 1990. ISBN 80-030-0330-X. (CS)
Recommended reading
NOSKIEVIČ, Petr. Modelování a simulace mechatronických systémů pomocí programu MATLAB SIMULINK. Ostrava: VŠB - Technická univerzita Ostrava, 2013. ISBN 978-80-248-3231-9.
(CS)
PELÁNEK, Radek. Modelování a simulace komplexních systémů: jak lépe porozumět světu. Brno: Masarykova univerzita, 2011. ISBN 978-80-210-5318-2. (CS)
ROSS, Sheldon M. Simulation. 3rd ed. San Diego: Academic Press, c2002. ISBN 01-259-8053-1. (EN)
PELÁNEK, Radek. Modelování a simulace komplexních systémů: jak lépe porozumět světu. Brno: Masarykova univerzita, 2011. ISBN 978-80-210-5318-2. (CS)
ROSS, Sheldon M. Simulation. 3rd ed. San Diego: Academic Press, c2002. ISBN 01-259-8053-1. (EN)
Classification of course in study plans
- Programme N-VSR-P Master's 1 year of study, summer semester, compulsory-optional
Type of course unit
Lecture
26 hod., optionally
Teacher / Lecturer
Syllabus
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.
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.
Computer-assisted exercise
26 hod., compulsory
Teacher / Lecturer
Syllabus
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
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