Design of Experiments and Optimization

Course content

Proper 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 Food and Biotech industry. 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 and sustainability. 

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

Education

MSc Programme in Food Science and Technology

Learning outcome

The course introduces the student to advanced design of experiment methods with focus on (food) industrial relevance. The software package used throughout the course is 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 and sustainability.

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.

See Absalon for a list of course literature

It is expected that the student have competences corresponding to a course in basic statistics.

Academic qualifications equivalent to a BSc degree is recommended.

Written
Oral
Individual
Collective
Continuous feedback during the course of the semester
ECTS
7,5 ECTS
Type of assessment
Oral examination, 20 min
Type of assessment details
The students will hand in a written (group or individual) report on assignment / project work. At the individual oral examination the students discuss the results from their project plus the curriculum / theory of the course with the examiners. No preparation time.

Weight: Oral examination in project report and curriculum 100%
Exam registration requirements

Hand in of written (group or individual) report on assignment / project work. 

Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Re-exam

Same as ordinary exam.

Possibility to re-submit project report two weeks before the date of the re-examination. 

Criteria for exam assessment

See Learning Outcome.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 40
  • Preparation
  • 55
  • Theory exercises
  • 40
  • Project work
  • 70
  • Exam
  • 1
  • English
  • 206

Kursusinformation

Language
English
Course number
LLEK10294U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Duration

1 block

Placement
Block 1
Schedulegroup
B
Capacity
50
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Studyboard
Study Board of Food, Human Nutrition and Sports
Contracting department
  • Department of Food Science
Contracting faculty
  • Faculty of Science
Course Coordinators
  • Franciscus Winfried J van der Berg   (2-6c68466c75756a34717b346a71)
  • Rasmus Bro   (2-7868466c75756a34717b346a71)
Saved on the 21-02-2024

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