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Course details
Student Mobility > Programmes and Courses > Courses in English > Course detailsDesign of Experiments
- Teaching: Completely taught in English
- ECTS: 5
- Level: Graduate
- Semester: Winter
- Prerequisites:
- None
- Load:
Lectures Exercises Laboratory exercises Project laboratory Physical education excercises Field exercises Seminar Design exercises Practicum 30 20 0 0 0 0 0 0 - Course objectives:
- Introduce students with basic principles of planning and analyzing and implementation of experiments in quality management. Show the meaning of experiment planning in optimizing processes and quality insurance.
- Student responsibilities:
- Grading and evaluation of student work over the course of instruction and at a final exam:
- Essay 50%, final exam 50%.
- Methods of monitoring quality that ensure acquisition of exit competences:
- Active participation in class.Continuous monitoring of participation in class and through homework. Checking understanding the subject matter through the partial exam and essay.
- Upon successful completion of the course, students will be able to (learning outcomes):
- After adopting the specific knowledge from the given course students will be able to: - identify the process and choose the appropriate DOE (design of experiment ) model - specify the shape of selected design using principles of DOE - carry out the experiment process by means that are derived from theory of DOE - analyse the data using modern statistical methods and software solutions - interpret the results - present the results in a way that is commonly used for conducted methodology
- Lectures
- 1. Design of experiment: basic terms, history and development of DOE Basic theory of samples. Systematization of E.P.
- 2. Variance analysis: one and more changeable factors. Decomposition of sum of squares.
- 3. Variance analysis - completely random experiment plan, and random blocks.
- 4. Analysis completely factorial models of experiment, linkage with regression.
- 5. Meaning interactions in factorial experiment planning. Experiment of higher rank. Experiment in several levels.
- 6. Movable (rotatable) DOE.Rotation of the axes.
- 7. Design of experiments with ""parcels"" and ""nests"".
- 8. Partial DOE-experiment 2k-p type. Generating contrasts, alias.
- 9. Linear regression: meaning of regression coefficients. Comparison of coefficients for two ore more regression equations.
- 10. Multiple regression, linear, nonlinear.
- 11. Special types of regression models.
- 12. Mathematical models: building model, stepwise regression.
- 13. Placket-Burman experiments.
- 14. Taguchi experiments. Orthogonal rows.
- 15. Design of experiment and process optimizing.
- Exercises
- 1. Arithmetic mean distribution, examples.
- 2. Analysis of variance, examples.
- 3. Analysis - random blocks models, examples.
- 4. Completely factorial DOE in two levels, examples.
- 5. Completely factorial DOE in several levels, examples.
- 6. Exam I.
- 7. Example of experiments with ""parcels"" and ""nests"".
- 8. Partial DOE, problems.
- 9. Linear regression, problems.
- 10. Exam II.
- 11. Examples of appliance of regression models, problems.
- 12. Examples of appliance of regression models, problems.
- 13. Placket-Burman DOE- problems.
- 14. Taguchi DOE- examples.
- 15. Exam III.
- Compulsory literature:
- Douglas C. Montgomery: "Design and Analysis of Experiments"
Robert F. Brewer: "Design of Experiments for Process Improvement and Quality Assurance"
Forrest W. Breyfogle III: "Statistical Methods for testing, Development, and Manufacturing" - Recommended literature:
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