Recommended prerequisite for participation in the module

Content, progress and pedagogy of the module

Learning objectives

Knowledge

Students who have passed the module should be able to

• Explain the establishment of experimental design with qualitative and quantitative factors
• Account for complete, partial and confounding 2k and 3k factorial experiments
• Explain incomplete block design and splitplot designs
• Explain how to perform control experiments, including the use of central points
• Account for orthogonal experimental design
• Describe methods of optimization of the experimental factors and minimizing noise factors 
• Account for regression analysis (including step-wise regression) of the drop in data
• Explain response surface design

Skills

• Develop study plans with qualitative and quantitative factors
• Perform control experiments
• Optimize the experimental factors
• Minimize the noise factors
• Use multiple analysis of variance and regression analyzes, including the combined variance and regression analyzes
• Analyze experimental data and be able to evaluate the methods used, validity and usefulness 
• Use statistical design of experiments in practice within the domain of quality / process optimization and to process the results by statistical methods on a computer

Type of instruction

Lectures and theoretical exercises

Extent and expected workload

150 hours

Exam

Exams