639-0925/06 – Design of Experiments (DOE)
| Gurantor department | Department of Quality Management | Credits | 10 |
| Subject guarantor | Ing. Mgr. Petra Halfarová, Ph.D. | Subject version guarantor | Ing. Mgr. Petra Halfarová, Ph.D. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2019/2020 | Year of cancellation | |
| Intended for the faculties | FMT, HGF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Knowledge of DOE basic terms and methods:
full factorial and fractional factorial plans,
robust product and process design,
analysis of real problems and their optimal solution,
application of one-way and two-way analysis of variance.
Ability to solve elementary DOE problems, using Excel and Statgraphics software
Teaching methods
Individual consultations
Project work
Summary
The subject Design of Experiments (DOE) expands the subject matter of regression analysis. Basic strategies of data preparation for regression models are discussed, as are full and fractional factorial plans. The emphasis is placed on the balance between statistical requirements and economic efficiency of data sampling. Construction of experimental plans is accompanied by the methodology of finding key inputs to the modelled process and their optimal set-up. The one-way and two-way analysis of variance (ANOVA) are also part of the subject. The generalizing chapters on dynamic planning and robust technology design are included.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Oral Exam
E-learning
Other requirements
1) Knowledge of DOE basic terms and methods: full factorial and fractional
factorial plans, robust product design
2) Analysis of real problems and their optimal solution
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Full Factorial Design at Two Levels.
2. Fractional Factorial Design at Two Levels.
3. Quadratic Models.
4. Blocking.
5. ANOVA.
6. Three-level Plans.
7. Box - Behnken Plan.
8. Dynamic Design of Experiments.
9. Designing Robust Products and Processes.
10.Quality characteristics
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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