639-0925/03 – 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 |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2013/2014 | Year of cancellation | |
| Intended for the faculties | HGF, FMT | 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
Coded variables Effect of factor, dispersion estimate of effect
factor,effect signifikance test Effect of factor graphic evaluation
Graph interaction
2. Fractional faktoriál design at two levels
Compozite design, finding of confounding patterns
Generator selections
3. Significant points of design
4. Second order response surface models Model determinig conditions
Test of curvature. Methods of determining second order response
surface models.Composite design.
Calculating the optimal level of significant factors
Box-Behnken design (BBD).Design for factors at three levels
5. Blocking in experimental design
6. ANOVA in DOE.Decomposition of residuals dispersion
Test Lack-of-fit.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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