450-4103/01 – Application of Modern Technologies in the Field of Industrial Automation (AMTOPA)

Gurantor departmentDepartment of Cybernetics and Biomedical EngineeringCredits5
Subject guarantordoc. Ing. Jan Žídek, CSc.Subject version guarantordoc. Ing. Jan Žídek, CSc.
Study levelundergraduate or graduateRequirementCompulsory
Study languageCzech
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFS, FEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
DAN0091 Ing. Lukáš Danys, Ph.D.
JAR0076 doc. Ing. René Jaroš, Ph.D.
KAH0017 doc. Ing. Radana Vilímková Kahánková, Ph.D.
Z1I40 doc. Ing. Jan Žídek, CSc.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 3+2
Part-time Credit and Examination 0+21

Subject aims expressed by acquired skills and competences

The aim of the course Application of Modern Technologies in the Field of Industrial Automation is ability to describe the concept of production lines built on the principles of Industry 4.0 resulting from the understanding and mastering of these principles and the new characteristics of modern production lines. The objective is qualified asking for cooperatation with experts in the relevant fields and technologies in the design and operation of these production lines.

Teaching methods

Project work


Students will get acquainted with the following principles of the Industry 4.0 concept: - basic principles and historical context of the Industry 4.0 concept - cloud technologies and their applications in industrial automation - Internet of Things and its Applications in Industrial Automation - collection and processing of data from industrial processes - collecting and analyzing image information - the use of virtual and augmenteded reality in industrial automation - incorporation of artificial intelligence methods into industrial automation - digital twin - robots as part of the production line - cyberphysical systems - case studies.

Compulsory literature:

1. SCHWAB, Klaus. The fourth industrial revolution. Geneva: World Economic Forum, [2016]. ISBN 978-1-944835-00-2 2. GILCHRIST, Alasdair. Industry 4.0: The Industrial Internet of Things. Imprint: Apress, 2016. ISBN isbn978-1-4842-2046-7 3. USTUNDAG, Alp; CEVIKCAN, Emre: Industry 4.0: managing the digital transformation. New York, NY: Springer Berlin Heidelberg, 2017. ISBN 978-3319578699

Recommended literature:

1. MATT, Dominik; MODRAK Vladimir; ZSIFKOVITS, Helmut:, Industry 4.0 for SMEs: Challenges, Opportunities and Requirements 1st ed. 2020 Edition. ISBN 978-3030254247

Way of continuous check of knowledge in the course of semester

Presentation of the results of partial tasks. Verification of acquired knowledge in the form of a test within the exam.


Other requirements

Participation in educational activities min. 80%.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Knowledge managent - new conditions for acquiring and developing knowledge in an era of rapid technological change. PLE & N 3.0 - an environment for coping with new concepts, technological and societal challenges, comparison with the traditional model of obtaining information through school, course, etc. Explanation of basic concepts and demonstration of tools. Getting Started with Portals Offering Courses, Demonstration of Industry 4.0: How to Revolutionize Your Business - The Honk Kong Polytechnic University (2018) Exercise Task: Finding and viewing videos (Youtube, edX, ...), communities, and industry resources for Industry 4.0 (https://www.youtube.com/watch?v=uNku3yd2tJA, http://theelearningcoach.com/elearning2 -0 / designing-personal-learning-environment / ...) 2. Introduction to the Problem - Historical Context of Industrial Revolutions, Basic Principles of the Fourth Industrial Revolution, Production Process Implementing Principles of Fourth Industrial Revolution - Basic Concept of Production Line. Task exercise: Presentation of the historical context, presentation of the basic principles of the fourth industrial revolution, finding references to information sources 3. Explaining concepts of data - information - knowledge. Means of data collection and processing in production processes, basic types of collected data, new generation sensors, tools for off-line analysis of collected data - examples of solutions, basic tasks in which data collected in production processes, structure of HW and SW resources used in production processes. Task exercise: Categorization of data collection tools, advantages and disadvantages of individual solutions 4. Cloud technologies and their applications in production processes - platform as a service - sample solutions. Comparison with the classic implementation of ICT resources into manufacturing processes at the level of classical industrial automation, the benefits, threats and disadvantages of cloud technologies, the world's largest cloud technologies suppliers. Exercise Task: to solve a standard task using cloud technologies. 5. IoT (Internet of Things) as part of the manufacturing process - technology, basic parameters, sample solutions. Need to transfer data in the technological process, development of technological progress in this area, interfaces and protocols, wire and wireless transmissions. Task exercise: Design of communication infrastructure for the production process in classical industrial automation, maximizing the use of technologies and IoT elements. 6. Processing of data collected in the production process - types of processing, basic statistical processing, interpolation and extrapolation of collected data, basic requirements for collected data (sampling, quantization), types of standard tasks, utilization of processed data. Task exercise: Presentation of data processing tools in the production process. 7. Working with image within production processes, optical inspection, basic structure of the optical inspection system. Typical data processing tasks in production processes. Example of type solutions Task exercise: Presentation of tools for processing measured data 8. Use of virtual and extended reality technology in production processes, basic tools, applications. Task for exercises: presentation of projects from VR and AR departments of the Department of Informatics - excursion to the laboratory. 9. Integrating artificial intelligence methods into data processing in production processes. Machine Learning - Explanation of the concept and demonstration of typical tasks using this data processing method. Task exercise: Presentation of tasks using machine learning methods and artificial intelligence in production processes 10. Digital twin as an abstract model of the production process. SW tools for the design, operation and maintenance of production lines. Explanation of the concept of a digital twin, a digital twin problem, the benefits of using a digital twin. Task exercise: Presentation of digital twin cases in the production process 11. Robots as part of a production line. Types of robots, ways of programming, typical tasks in which the robot replaces in a man's manufacturing process. Task For Exercise: Excursion to the Laboratory of the Department of Robotics at FS. 12. Cyberphysical system as the basic building unit of the production line. Characteristics, properties, product role, personalization of production, ... Production line concept based on principles Industry 4.0. Task For Exercise: An Excursion on a Modern Industrial Line Created on Principles Industry 4.0. 13. - 14. Case studies of production lines built according to the principles of Industry 4.0, conceptual design of the production line on industry principles 4.0, explanation of the correspondence of the principles of industry 4.0 and their implementation in the production process, design of other sources of information for the development of knowledge presented in the subject, essential information.

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 40  20
        Examination Examination 60  10 3
Mandatory attendence participation: 80% attendance at the exercises

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Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (N0688A140014) Industry 4.0 PKS P Czech Ostrava 1 Compulsory study plan
2024/2025 (N1041A040013) Intelligent transport and logistics P Czech Ostrava 1 Compulsory study plan
2024/2025 (N1041A040013) Intelligent transport and logistics K Czech Ostrava 1 Compulsory study plan
2023/2024 (N0688A140014) Industry 4.0 PKS P Czech Ostrava 1 Compulsory study plan
2023/2024 (N1041A040013) Intelligent transport and logistics P Czech Ostrava 1 Compulsory study plan
2023/2024 (N1041A040013) Intelligent transport and logistics K Czech Ostrava 1 Compulsory study plan
2022/2023 (N0688A140014) Industry 4.0 PKS P Czech Ostrava 1 Compulsory study plan
2021/2022 (N0688A140014) Industry 4.0 PKS P Czech Ostrava 1 Compulsory study plan
2020/2021 (N0688A140014) Industry 4.0 PKS P Czech Ostrava 1 Compulsory study plan
2019/2020 (N0688A140014) Industry 4.0 PKS P Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction

2023/2024 Winter
2022/2023 Winter
2021/2022 Winter
2020/2021 Winter