LLEK10294U Design of Experiments and Optimization
Volume 2013/2014
Education
MSc in Food Science and
Technology. Specialization in Process Analytical Technology.
The course is listed as limited elected study in the Food Science and Technology.
The course is listed as limited elected study in the 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.
It is expected that the student have competences corresponding to a course in basic statistics.
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.
It is expected that the student have competences corresponding to a course in basic statistics.
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
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.
Workload
- Category
- Hours
- Exam
- 8
- Lectures
- 40
- Preparation
- 48
- Project work
- 70
- Theory exercises
- 40
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 20 minutesDescription of Examination: 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% - Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
Criteria for exam assesment
See Learning Outcome
Course information
- Language
- English
- Course code
- LLEK10294U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- B
- Course capacity
- 50
- Continuing and further education
- Study board
- Study Board of Food, Human Nutrition and Sports
Contracting department
- Department of Food Science
Course responsibles
- Franciscus Winfried J van der Berg (2-69654369727267316e7831676e)
Saved on the
30-04-2013