Reliability Modeling and Analysis

2018/2019

Prerequisite/Recommended prerequisite for participation in the module

Probability, statistics and stochastic processes

Content, progress and pedagogy of the module

Purpose

The course purpose consists of two parts:

  • To contribute to students’ attainment of comprehension of fundamental principles for reliability modelling
  • To contribute to students’ attainment of comprehension of fundamental principles for reliability analysis

Content

  • Principles of reliability modelling
    • Quality and reliability
    • Creating reliability vs. measuring reliability
    • Failure modes, causes and mechanisms
  • Probabilistic models of failure phenomena
    • Essentials of probability theory
    • Probabilistic definition of reliability
  • Component reliability
    • Common distribution in component reliability
    • Component reliability model selection
  • System reliability analysis
    • Structure analysis and design
    • Reliability block diagram method
    • Fault modes and effects analysis
    • Fault tree analysis
  • Hazard and risk analysis
  • Reliability analysis of dynamic systems
    • Markov theory and applications
    • Simulation methods (Monte Carlo methods)
    • Analysis of fault tolerant systems
  • Bayesian analysis
    • Foundations of Bayesian statistical inference
    • Bayesian inference in reliability
    • Performing Bayesian reliability analysis
    • Bayesian decision and estimation theory
  • Uncertainty analysis and propagation methods
    • Measuring uncertainty
    • Uncertainty propagation
  • Reliability in computer systems
    • Hardware reliability vs. software reliability
    • Software reliability improvement methods
    • Software reliability assessment methods

Learning objectives

Knowledge

  • Have comprehension of fundamental principles for reliability modelling and analysis
  • Have comprehension of  reliability analysis using logic diagrams
  • Have comprehension of Bayesian methods for simple reliability modelling and analysis

Skills

  • Be able to apply probabilistic methods for reliability modelling and analysis.
  • Be able to judge the usefulness of the set up methods
  • Be able to relate the methods to applications in the industry

Competences

  • Independently be able to define and analyze scientific problems within the area of reliability modelling and analysis.
  • Independently be able to be a part of professional and interdisciplinary development work within the area of reliability modelling and analysis.

Type of instruction

The program is based on a combination of academic, problem-oriented and interdisciplinary approaches and organized based on the following work and evaluation methods that combine skills and reflection:

  • Lectures
  • Classroom instruction
  • Project work
  • Workshops
  • Exercises (individually and in groups)
  • Teacher feedback
  • Reflection
  • Portfolio work

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 examReliability Modeling and Analysis
Type of exam
Written or oral exam
ECTS5
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentAs stated in the Joint Programme Regulations.
http:/​/​www.engineering.aau.dk/​uddannelse/​studieadministration/​

Facts about the module

Danish titlePålidelighedsmodellering og analyse
Module codeN-IRS-K2-4
Module typeCourse
Duration1 semester
SemesterSpring
ECTS5
Empty-place SchemeYes
Location of the lectureCampus Esbjerg
Responsible for the module

Organisation

Study BoardStudy Board of Energy
FacultyFaculty of Engineering and Science