PhD in Industrial Engineering
Liberec, Czech Republic
DURATION
4 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
15 Feb 2025*
EARLIEST START DATE
Sep 2025
TUITION FEES
USD 2,000 / per year
STUDY FORMAT
On-Campus
* 1st round | June 28, 2025 (2nd round)
Introduction
The objective of the proposed PhD programme Industrial Engineering is to prepare university-educated top specialists in research, development and applications in quality management, experiment design, forecasting, implementation of Industry 4.0 (the Fourth Industrial Revolution) principles and comprehensive statistical data analysis, particularly in industrial applications dealing with fibre structures. The structure and curriculum of the course respond to the industry demand for specialist qualified staff focusing on product innovation including the innovations of high-order and the improvement / functionalisation of production systems and processes while complying with requirements for sustainability and efficient waste utilisation. These needs stem from the accelerated development of new technologies with respect to a reduction in environmental and energy-related issues as forecasts based on the current situation point out for them to be of key importance for the future.
Admissions
Curriculum
1. semester
- Applied Mathematics (Selected Topics) (compulsory optional)
- Mathematical Statistics (compulsory optional)
- Planning and Quality Control (compulsory optional)
- Project MGMT to Implement Innovations (compulsory optional)
2. semester
- (Application of Random Processes (compulsory optional)
- Image Processing and Analysis (compulsory optional)
- Mathematical Principles of Forecasting (compulsory optional)
- Planning and Evaluation of Experiments (compulsory optional)
- Selected Parts of Quality Control (compulsory optional)
- Special Methods of Quality Evaluation (compulsory optional)
3. semester
- Computer Modeling of Technical Systems (compulsory optional)
- Evaluation and Quality Metrics (compulsory optional)
- Macromolecular Chemistry (compulsory optional)
- Optics of Solids (compulsory optional)
- Practical Stereology (compulsory optional)
- Quality of Fibrous Products (compulsory optional)
- Reliability and Risk Assessment (compulsory optional)
- Sorption Processes (compulsory optional)
- Structural Mechanics of Fibrous Ass. (compulsory optional)
- Textile Chemistry (compulsory optional)
- The Finite Element Method (compulsory optional)
- Theory and Application of Machine Vision (compulsory optional)
4. semester
- Comfort of Clothes (compulsory optional)
- Composites and Nanocomposites (compulsory optional)
- Designing of Fibrous Products (compulsory optional)
- Electronics in Textile Structures (compulsory optional)
- Market Research and Customer Satisfactio (compulsory optional)
- Sensorical Textile Materials (compulsory optional)
- Simulation of the Apparel Processes (compulsory optional)
- Technology of Nanofibers Production (compulsory optional)
- Testing theory and experimental data tre (compulsory optional)
- Wetting of Fibrous Materials (compulsory optional)
5. semester
- Experimental technique of the textile (compulsory)
6. semester
- Specialization in Field (compulsory)
- Courses without specified study plan
- Economics and Organizations Management (compulsory optional)
- Hydrodynamics Process of Spinning (compulsory optional)
- Intership Abroad I (optional)
- Intership Abroad II (optional)
- Intership in a Company I. (optional)
- Intership in a Company II. (optional)
Program Outcome
Graduates from the Industrial Engineering PhD course will have a thorough specialist knowledge of their field (product and technology process quality management, comprehensive high-order innovation development and implementation of methods using computer-assisted data mining production concepts) to allow them to apply creative and research work in the field. Graduates will have mastered modern principles of designing and managing technical projects, with a focus on the development of high-order innovation. They will be able to prepare, lead and evaluate such projects. They will have developed their communication skills and be able to follow through their ideas and views. They will be thoroughly familiar with data handling methodologies using computer-assisted approaches referred to as soft computing. They will be prepared to implement the techniques and tools of Industry 4.0 into practical applications. They will also be able to quickly adapt to demanding work in other fields and interdisciplinary research. They will be poised to continue their skill growth independently and comprehensively deal with complex research, technical and engineering issues.