352-0559/01 – Digital factory 2.0 (DT20)
| Gurantor department | Department of Control Systems and Instrumentation | Credits | 5 |
| Subject guarantor | Ing. David Fojtík, Ph.D. | Subject version guarantor | Ing. David Fojtík, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 2 | Semester | winter |
| | Study language | Czech |
| Year of introduction | 2022/2023 | Year of cancellation | |
| Intended for the faculties | FS | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
The aim of this subject is to familiarize students with the principle of a digital factory, including practical introduction to the means, technologies and methods, which they form the backbone of the digital factory. Students get acquainted with the problems of typical sensors, communications networks, data storage and processing methods and data evaluation including an introduction to artificial intelligence.
Teaching methods
Lectures
Tutorials
Summary
The subject introduces students with the principles of digital factories, as well as the devices, technologies and methods that form the backbone of the digital factory.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
The students has to solve and defend an individual project. (50 points)
Knowledge test. (50 points)
E-learning
Other requirements
User knowledge of computing.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Introduction to the Subject, Design and Structure of the Digital Factory.
2. Introduction to smart sensors and sensors with a focus on transport and handling.
3. Introduction to contactless and optical sensors.
4. Introduction to image data processing.
5. The Internet of Things and its importance in the digital factory.
6. Computer data networks in digital factories.
7. Wireless computer networks in digital factories.
8. Industrial communication standards and communication protocols.
9. Introduction to Relational Databases and SQL Server.
10. TSQL Basics - Data mining and evaluation.
11. Digital twin, implementation in digital factory.
12. Automatic data evaluation and introduction to artificial intelligence.
13. Neural networks, types of neural networks, training methods.
14. Granting credits.
Conditions for subject completion
Conditions for completion are defined only for particular subject version and form of study
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.