Course detail

Modelling and Simulation of Production Systems

FSI-GMV-KAcad. year: 2021/2022

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

Ing. Jiří Kovář, Ph.D.

Department

Institute of Production Machines, Systems and Robotics (ÚVSSR)

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.

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.).

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.

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.

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

A. Alan B. Pritsker, Claude D. Pegden: Introduction to Simulation and SLAM II
AIM Manuals
Averill M. Law, W. David Kelton: Simulation Modeling and Analysis
Jerry Banks, Discrete-Event System Simulation

Recommended reading

Kuneš Jozef a kol.: Základy modelování ,SNTL , 1989
Neuschl Štefan a kol.: Modelovanie a simulácia, ALFA, 1989
Zítek Pavel: : Simulace dynamických systémů , SNTL, 1989

Classification of course in study plans

  • Programme N-VSR-K Master's 1 year of study, summer semester, compulsory-optional

Type of course unit

 

Guided consultation in combined form of studies

17 hod., compulsory

Teacher / Lecturer

Ing. Jiří Kovář, Ph.D.

Syllabus

1. Introduction to modeling and simulation of systems. Analysis and classification of systems.
2. Basic concepts of systems theory. Classification of models. Basic methods of modeling continuous and discrete systems. Software possibilities of system modeling.
3. Mathematical foundations of modeling and simulation.
4. Methods of modeling discrete systems.
5. Methods of modeling discrete systems.
6. Methods of modeling discrete systems.
7. Methods of event controlled simulation, creating and using of calendar events
8. Modeling of stochastic systems, using of statistical methods, generation of random variables.
9. Connections of real technical systems of production systems in discrete simulation.
10. Connections of real technical systems of production systems in discrete simulation.
11. Evaluation and visualization of simulation results.
12. Interconnection of real and simulated systems, data exchange, model verification.
13. Current trends in modeling and simulation of systems

Guided consultation

35 hod., optionally

Teacher / Lecturer

Ing. Jiří Kovář, Ph.D.

Syllabus

1. Simulation languages, overview of basic tools for description of models and experiments. Basic principles of implementation of simulation systems.
2. Continuous modeling - creating a model and working with it.
3. Continuous modeling - creating a model and working with it.
4. Discrete modeling, event-driven modeling, preparation and creation of models.
5. Discrete modeling, event-driven modeling, preparation and creation of models.
6. Discrete modeling, event-driven modeling, preparation and creation of models.
7. Methods of connecting continuous and discrete modeling.
8. Methods of connecting continuous and discrete modeling.
9. Formal requirements for the model as part of the supply chain
10. Formal requirements for the model as support for the management of production systems
11. Student project - assignment.
12. Methods of modeling production systems under the condition of using typical sensory data; ways of connecting the model with data in off-line and on-line mode in the context of Industry 4.0; Using the model for design and planning.
13. Student project review