Skip to main content

Before choosing course

The overall purpose of the course is that the student should be well acquainted with basic concepts, theory, models and solution methods in reliability theory. The student should have training in analysing reliability models and apply these models to real examples.

Course offering missing for current semester as well as for previous and coming semesters
* Retrieved from Course syllabus SF2937 (Autumn 2007–)

Content and learning outcomes

Course contents

Hazard rates and life length distributions. Analysis of survival data. Estimation of hazard rates and survival functions for survival data. Optimal maintenance strategies.

Markov models for reliability systems. Markov processes with discrete state spaces. Poisson processes. Semi-Markov processes. Renewal theory.

Structure functions and fault trees. Combination of systems. Measures of structural and reliability importance of components. Associated random variables.

Intended learning outcomes

To pass the course, the student should be able to do the following:

  • construct and analyse reliability models for simple technical systems in terms of concepts like component wise and system wise redundancy, and series and parallel structures
  • describe standard models and explain the applicability of the models in given examples, in particular renewal processes
  • construct simple Markov models for technical systems and explain their properties and behaviour
  • with standard methods like Kaplan-Meier and Nelson estimate the hazard rate for survival data, possibly censored
  • med Weibull analysis analyse survival data and determine optimal strategies for maintenance
  • construct structure functions and fault trees as models for technical systems and calculate different measures of reliability for the components in the systems
  • for systems with dependent components approximate the system availability using standard methods and inequalities

To receive the highest grade, the student should in addition be able to do the following:

  • Combine all the concepts and methods mentioned above in order to solve more complex problems.

Course Disposition

No information inserted

Literature and preparations

Specific prerequisites

SF1901 (5B 1501) Probability theory and statistics I or equivalent.

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

Holen, Höyland & Rausand: Pålitelighetsanalyse, Tapir

Enger, Grandell: Markovprocesser och köteori, Compendium

Complementary material from the department.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • INL1 - Assignments, 1,5 hp, betygsskala: P, F
  • TEN1 - Examination, 6,0 hp, betygsskala: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

No information inserted

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web SF2937

Offered by

SCI/Mathematics

Main field of study

No information inserted

Education cycle

Second cycle

Add-on studies

No information inserted

Supplementary information

Not given 12/13.