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LLEK10294U  Design of Experiments and Optimization Volume 2014/2015

Course information

LanguageEnglish
Credit7,5 ECTS
LevelFull Degree Master
Duration1 block
Placement
Block 1
Schedule
B (Mon 8-12 + Tues 13-17 + Fri 8-12)
Course capacitymax. 50
Continuing and further education
Study boardStudy Board of Food, Human Nutrition and Sports
Contracting department
  • Department of Food Science
Course responsible
  • Franciscus Winfried J van der Berg (2-6a66446a737368326f7932686f)
Saved on the 27-02-2015
Education
MSc Programme in Food Science and Technology
Content

Basic design of experiments is an essential part of any scientific investigation. As such statistical process design, monitoring and control are an integral part of the PAT concept. In this course the connection between theory and production process practice will be at the forefront.

The methods studied in this course will vary from year to year but each year the main topics are: statistical inference, (fractional) factorial design, computer generated design, Quality by Design, evolving operation, process/product optimization, measurement optimization, and optimization towards process robustness. 

Computer exercises of simulated and real data using JMP are an integrated part of the course. The student will receive an introduction to both programs.

Learning Outcome

The course introduces the student to advanced design of experiment methods with focus on Process Analytical Technological (PAT) relevance. The software package used throughout the course are JMP.

After completing the course the student should be able to:
Knowledge:
Summarize basic and advanced design of experiment methods
Summarize basic and advanced process optimization methods
Summarize basic and advanced statistical process control methods

Skills:
Perform statistical inference
Use (fractional) factorial design, advanced design methods and computer generated designs
Analyze experimental design data

Competences:
Use and perform Quality by Design
Use and perform process/product optimization methods
Use and perform measurement optimization
Use and perform optimization towards process robustness

Literature

Book chapters (electronically available), scientific papers and course notes will be provided.

Teaching and learning methods
The students will be introduced to the theory through lectures. The students will work individually and in groups on a data analytical problem using the taught concepts and software to analyze a problem. The results are formulated in a written report which is orally presented at a seminar at the end of the course.
Academic qualifications
It is expected that the student have competences corresponding to a course in basic statistics
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Exam
Credit7,5 ECTS
Type of assessment
Oral examination, 20 min
The students will hand in a written group report on project work. At the oral examination the student discuss the results from their projects and the theory taught in the course with the examiners

Weight: Oral examination in project report and curriculum 100%
Exam registration requirementsHand in of written group report on project work
AidAll aids allowed
Marking scale7-point grading scale
Censorship formNo external censorship
More than one internal examiner
Criteria for exam assesment

Fullfilment of the learning outcomes

Workload
CategoryHours
Lectures40
Theory exercises40
Project work70
Preparation55
Exam1
Total206
Saved on the 27-02-2015