Course detail

Digitalization in Industry

FSI-VI4Acad. year: 2026/2027

The course introduces students to modern concepts, technologies and processes that define today’s digitally driven industrial environment (Industry 4.0). Students gain an understanding of cyber-physical systems, Internet of Things (IoT), digitalization of production and logistics, digital twins, automation and robotics, as well as the role of data and artificial intelligence in optimizing manufacturing operations. The aim is to equip students with the knowledge required to understand the technological and systemic aspects of industrial digitalization, assess its impact on production, design and operation, and actively participate in the digital transformation of manufacturing enterprises.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. Ing. Zdeněk Hadaš, Ph.D.

Department

Institute of Automation and Computer Science (ÚAI)

Entry knowledge

The usual secondary school computer literacy is supposed.

Rules for evaluation and completion of the course

Classified credit: Active participation in the seminars, elaboration of a given project, practical test and oral presentations.

Attendance at seminars is controlled. An absence can be compensated for via solving additional problems.

Aims

Upon successful completion of the course, students will be able to:

  • define the main principles and motivations behind industrial digitalization and identify key Industry 4.0 components (cyber-physical systems, IoT, digital twins, automation, robotics, data analytics);

  • identify opportunities to use digital technologies in production and logistics, and evaluate their impact on productivity, flexibility, quality and costs;

  • gain basic practical skills in designing of IoT sensing technologies within an industrial context;

  • critically evaluate the challenges of implementing digitalization, including security, data quality, workforce aspects and organizational transformation.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

HANKEL, M.: Industrie 4.0: The Reference Architectural Model Industrie 4.0 (RAMI 4.0). ZVEI, Frankfurt am Main, 2015
Lee et al.: A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems, Manufacturing Letters, Volume 3, January 2015, Pages 18-23  (EN)
Tao et al: Digital Twin in Industry: State-of-the-Art, IEEE Transactions on Industrial Informatics ( Volume: 15, Issue: 4, April 2019) (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme B-STR-P Bachelor's

    specialization AIŘ , 3 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Ing. Zdeněk Hadaš, Ph.D.

Syllabus

  • Introduction to industrial digitalization – definitions, motivations, historical overview (industrial revolutions to Industry 4.0)
  • Digital Twin and simulation of manufacturing processes
  • Key technologies of digitalization – IoT, sensors, data acquisition, communication technologies, edge and cloud computing
  • Cyber-physical systems and IT/OT integration – linking production technologies with information systems
  • Automation, robotics and flexible manufacturing in the context of digitalization
  • Data, analytics and artificial intelligence in manufacturing – data acquisition, preprocessing, analysis, predictive maintenance
  • Logistics and digitalization
  • Interoperability, standards and security in digital industry – protocols, cybersecurity, data protection
  • Implementing digitalization – strategy, phases, KPIs, evaluation
  • Sustainability, ecology and digital manufacturing – reducing energy/material consumption, circular economy
  • Future trends – Industry 5.0, autonomous cells, full-factory digital twins, AI-driven manufacturing
  • Industrial case studies – successful digitalization projects from practice

Computer-assisted exercise

26 hod., optionally

Teacher / Lecturer

prof. Ing. Zdeněk Hadaš, Ph.D.

Syllabus

  • Analysis of current state of digitalization in Czech manufacturing
  • Designing a simple IoT system for (what to measure, how to transmit data, what to do with them)
  • Working with data from IoT sensors
  • Design of a digital twin, virtual commissioning
  • Analysis of a flexible production cell for a small series, use of a robot/automation + digitalization
  • Dataset from production (or simulated) and analysis: identify weak points, propose a predictive maintenance method
  • Mapping of logistics and value streams in the company
  • Case study - what happens when the production system is not safe, proposal of measures
  • Digitalization implementation plan for a small manufacturing company: goals, metrics, risks •
  • How digitalization can reduce the environmental impact in production
  • Presentation "My vision for the factory of 2035"