Course detail
Industrial digitalization and AI
FSI-HME Acad. year: 2026/2027 Summer semester
The course offers students an introductory yet practically oriented overview of the concepts, technologies and processes of modern industrial environments characterised by digitalization, the integration of production and information technologies, and the use of advanced manufacturing technologies (so-called Industry 4.0). The emphasis is placed particularly on applications in mechanical engineering technologies – machining, forming and welding.
Students will gain a basic overview of cyber-physical systems, the Internet of Things (IoT), digitalization of manufacturing and logistics processes, digital twins, automation and robotization of workplaces, and the role of data and artificial intelligence in the optimisation of industrial processes.
The aim is that graduates understand both the technological and system context of industrial digitalization, consider its impact on production, maintenance and operations, and are able to actively participate in the digital transformation of manufacturing enterprises.
Supervisor
Department
Learning outcomes of the course unit
Prerequisites
Basic knowledge of material handling, production automation. The student must have an overview of the machines and equipment used in engineering technologies, especially in forming, machining, welding, casting and unconventional technologies, and know their application in practice.
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Attendance at lessons is checked. Only one lecture may be missed without penalty. In the case of more missed exercises and the impossibility of replacing the exercise, the substitute projects and computational work will be assigned.
Participation in lessons is controlled by solving the partial projects submitted in the form of protocols. The subject-unit credit is done by examining the participation in the course and the projects evaluation. The exam consists of the written test and the oral part.
Language of instruction
Czech
Aims
After successfully completing the course, the student will:
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understand the main principles and motivations for the digitalization of industrial manufacturing systems and know the key components of the Industry 4.0 concept (e.g. cyber-physical systems, IoT, digital twins, robotization, automation, data analytics), with a specific focus on machining, forming and welding technologies;
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be able to identify opportunities for using digitalization technologies in production and logistics, and evaluate their impact on productivity, flexibility, quality and costs of technological processes;
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acquire basic practical skills in the design and use of IoT sensors and basic data analysis in an industrial context;
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be prepared to critically assess implementation aspects of digitalization, especially data and system security, data quality, and changes in work procedures and organisational structure of manufacturing companies.
Specification of controlled education, way of implementation and compensation for absences
The study programmes with the given course
Programme N-STG-P: Manufacturing Technology, Master's
branch STG: Manufacturing Technology, 4 credits, compulsory
Programme N-STG-P: Manufacturing Technology, Master's
branch STM: Manufacturing Technology and Management in Industry, 4 credits, compulsory
Type of course unit
Lecture
39 hours, optionally
Syllabus
Introduction to digitalization in industry – definitions, motivation, historical development (from industrial revolutions to Industry 4.0).
Digital twin and simulation of manufacturing processes.
Key digitalization technologies – IoT (Internet of Things), sensors and data acquisition, communication technologies, edge and cloud computing.
Cyber-physical systems and production IT/OT integration – interconnection of manufacturing systems and information technologies.
Automation, robotization and flexible production within digitalization.
Data, analytics and artificial intelligence in manufacturing – data collection, preprocessing, analysis, predictive maintenance.
Logistics and digitalization.
Exercise
26 hours, compulsory
Syllabus
Digitalization
Introductory exercise to the course, motivation for digitalization and AI in manufacturing technologies, introduction of semester project requirements.
Presentations
Short student presentations on selected applications of digitalization / AI in machining, forming or welding.
UST presentation – Digital lab tour
Presentation of UST laboratories and selected industrial projects in digitalization, robotization and intelligent manufacturing systems.
VR and DT (Digital Twin)
Demonstrations of the use of virtual reality and digital twins for the design, simulation and visualisation of manufacturing cells and technological processes.
Industrial robot KUKA, ABB
Practical work with an industrial robot – basic programming, demonstration of typical handling tasks in manufacturing.
Collaborative robot Fanuc, ABB
Exercise focused on collaborative robots (HRC): programming, safety, integration into a technological workplace.
IoT
Use of the Raspberry Pi platform as a simple IoT node – data acquisition and transfer from a technological device, basic visualisation.
Material handling C2 – logistics, cranes
Digital support of material handling and logistics in hall C2: cranes, lifting equipment, tracking of material flows.
MES/ERP digitalisation
Demonstration and basic work with a MES system – monitoring of production, orders and machines, simple OEE evaluation.
Industry 4.0 practices
Practical exercise led by an external expert / partner company (Holoubek) focused on real examples of implementing digitalization and automation.
Digital warehouse
Demonstration of a digitally controlled warehouse – barcodes and RFID, material and semi-finished product tracking, connection to the manufacturing system.
Credit (course completion)
Credit-granting exercise: practical test and oral / group presentation of semester projects.