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Course title -
Course code MUPI/4IPP
Organizational form of instruction Lecture
Level of course unspecified
Year of study not specified
Semester Winter and summer
Number of ECTS credits 0
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Chromjaková Felicita, prof. Ing. PhD.
Course content
1. Industrial engineering - essence of the discipline, development concepts (Ford production system, Baťa concept, Toyota Production System, Fractal factory, Industry 4.0). 2. Analysis of industrial engineering methods and tools from the point of view of quantitative and qualitative methods of scientific research, data analysis methodology and the system concept of e-reporting for the purposes of designing, managing and organizing industrial engineering processes. 3. Innovative concepts of WOIS, TRIZ, Ideen Management, Smart Technology - implementation in projects in industrial engineering. 4. Project-driven digital enterprise - selected methods of the Industry 4.0 concept oriented to process and project approaches to organization, management and innovation processes in modern companies with the support of smart technologies. 5. Analysis of scientific approaches and practical project solutions from the point of view of research solution of projects in industrial engineering.

Learning activities and teaching methods
  • Participation in classes - 10 hours per semester
  • Home preparation for classes - 15 hours per semester
  • Home preparation for classes - 15 hours per semester
  • Participation in classes - 10 hours per semester
prerequisite
Knowledge
Completion of professional subjects in the fields of study Economics and Management, Industrial Engineering. Ability to identify, analyze and process process data for analytical purposes. Knowledge of statistics and mathematical modeling. Detailed knowledge of the areas of designing production systems and processes. Detailed knowledge of the design of logistics and support processes.
Completion of professional subjects in the fields of study Economics and Management, Industrial Engineering. Ability to identify, analyze and process process data for analytical purposes. Knowledge of statistics and mathematical modeling. Detailed knowledge of the areas of designing production systems and processes. Detailed knowledge of the design of logistics and support processes.
Completion of professional subjects in the fields of study Economics and Management, Industrial Engineering. Ability to identify, analyze and process process data for analytical purposes. Knowledge of statistics and mathematical modeling. Detailed knowledge of the areas of designing production systems and processes. Detailed knowledge of the design of logistics and support processes.
Completion of professional subjects in the fields of study Economics and Management, Industrial Engineering. Ability to identify, analyze and process process data for analytical purposes. Knowledge of statistics and mathematical modeling. Detailed knowledge of the areas of designing production systems and processes. Detailed knowledge of the design of logistics and support processes.
learning outcomes
Identifies key concepts and their essence in industrial engineering Can use selected methods and tools of industrial engineering for systematic research of selected dependencies and contexts when solving projects in production processes. Can use mathematical-statistical methods to implement system data analysis. It can integrate metrics and indicators into the system model environment. It is able to set the rules of operation of the production system. He has knowledge of managerial organization and system model management.
Identifies key concepts and their essence in industrial engineering Can use selected methods and tools of industrial engineering for systematic research of selected dependencies and contexts when solving projects in production processes. Can use mathematical-statistical methods to implement system data analysis. It can integrate metrics and indicators into the system model environment. It is able to set the rules of operation of the production system. He has knowledge of managerial organization and system model management.
teaching methods
Activating (Simulation, games, dramatization)
Activating (Simulation, games, dramatization)
Skills
Methods for working with texts (Textbook, book)
Methods for working with texts (Textbook, book)
Monologic (Exposition, lecture, briefing)
Monologic (Exposition, lecture, briefing)
Teamwork
Teamwork
assessment methods
Knowledge
Analysis of educational material
Analysis of educational material
Essay
Essay
Composite examination (Written part + oral part)
Composite examination (Written part + oral part)
Recommended literature
  • BIDANDA,B. Maynard?s Industrial and Systems Engineering ? Handbook. McGraw Hill, 2022. ISBN 978-1260461565.
  • CHROMJAKOVÁ, F., TUČEK, D., BOBÁK, R. Projektování výrobních procesů pro Průmysl 4.0.. Zlín: Univerzita Tomáše Bati ve Zlíně, 2017. ISBN 978-80-7454-680-8.
  • VINE, M. Handbook of Industrial Engineering. Clanrye International, 2015. ISBN 978-163240274-5.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester