Prerequisite/Recommended prerequisite for
participation in the module
The module is based on knowledge achieved in Probability Theory,
Stochastic Processes and Applied Statistics on 1st semester of
Master of Science study programme in Energy Engineering, Master of
Science study programme in Sustainable Energy Engineering, or
similar.
Content, progress and pedagogy of the
module
Learning objectives
Knowledge
- Have comprehension of the fundamental concepts, terms and
methods used within optimisation
- Have comprehension of the fundamental concepts, terms and
typical methods used within numerical optimisation of linear and
nonlinear optimisation problems
- Have gained an in‐depth understanding of important concepts and
methods of optimisation for efficient solution of optimisation
problems within different areas of engineering
- Have comprehension of how to apply reliability and robust
design approach during product development
- Understand statistics that support robustness and
reliability
- Have knowledge about cost of poor quality in a product
lifetime
- Be able to establish mission profile for different applications
and use it into the useful reliability context
- Understand difference between preventive scheduled maintenance
or by degradation
- Have comprehension of stressor components like temperature,
humidity, vibration and their impact
- Be able to model and determine life-time of components
- Understand physics of failure approach and also failure
mechanism – both in normal operations and beyond
- Have knowledge about qualitative and quantitative test methods
for reliability assessment
- Have knowledge about prognostic methods and real‐time
monitoring in power electronic systems
Skills
- Be able to use optimisation concepts and topics
- Be able to use numerical methods of unconstrained
optimisation
- Be able to use numerical (mathematical programming) methods for
optimisation of multidimensional functions with constraints
- Be able to solve multiobjective optimisation problems
- Be able understand how designs fit into the robustness
validation concept
- Be able to set up simple methods for reliability targets and
field analysis
- Be able to set up lifetime requirement at function level or
component level
- Have knowledge of how to use test methods for reliability and
robustness assessment
Competences
- Be able to account for the considerations involved in the
process of formulating and solving engineering optimisation
problems, choosing an advantageous method of solution and
implementing it in practice.
- Be able to build a system reliability model
- Set up design limits in respect to reliability
- Be able to specify test procedures for new product
development
Type of instruction
The form(s) of teaching will be determined and described in
connection with the planning of the semester. The description will
account for the form(s) of teaching and maybe accompanied by an
elaboration of the roles of the participants. The programme is
based on a combination of academic, problem oriented and
interdisciplinary approaches and organised based on the following
types of instruction that combine skills and reflection:
- lectures
- project work
- workshops
- exercises (individually and in groups)
- e-learning in different ways such as flipped class-room,
blended learning, game or quiz, etc.
- teacher feedback
- reflection
- portfolio work
- study circle
- self-study
Extent and expected workload
Since it is a 5 ECTS course module, the work load is expected to
be 150 hours for the student.
Exam
Exams
Name of exam | Optimisation Theory and Reliability |
Type of exam | Written or oral exam |
ECTS | 5 |
Assessment | 7-point grading scale |
Type of grading | Internal examination |
Criteria of assessment | The criteria of assessment are stated in the Examination
Policies and Procedures |