Entry requirements

60 credits within the Bachelor's Programme in Industrial Engineering and Development, including Introduction to Quality Technology for Engineers and Statistics for Engineers.

Learning outcomes

After completing the course, students should be able to:

• describe how statistical methods can be used for quality development in industrial companies
• design and evaluate factorial designs for full and fractional two-level design of experiments
• give an account of the effect of noise factors on production processes
• apply methods to eliminate noise factors
• discuss how sustainability parameters can be integrated in statistical quality control and industrial design of experiments
• design models for the outcome of processes and validate these.

Content

Different statistical engineering tools in the field of quality technology where application of different tools to different processes is central. The focus is on industrial design of experiments, including, for example, factorial designs for full, fractional and repeated two-level experimental designs. Concepts and methods in design of experiments such as residuals, interaction diagrams, models, randomised designs, blocking, Kackers graph and robust parameter design. Statistical quality control. Sustainability parameters. Application of computer aid for calculations.

Instruction

Lectures, exercises, seminars and laboratory sessions.

Assessment

Written examination (3 credits). Laboratory sessions and written assignments (2 credits).

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding targeted pedagogical support from the University's disability coordinator.

Other regulations

The course may not be included in a degree together with 1TG254 Statistical Quality Control and Trial Design.