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FMF3028 Robust and Probabilistic Design 6.0 credits

Course offerings are missing for current or upcoming semesters.
Headings with content from the Course syllabus FMF3028 (Autumn 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Engineering statistics: Normal, exponential and Weibull distribution, confidence interval.

Statistical experimental design: physical experiments and simulations, censored and suspended test.

Probabilistic design; Monte Carlo simulations (with Matlab and Ansys) of variation of performance caused by variations in design - manufacturing tolerances, material properties, geometric configuration), user (anthropometric data) and environment parameters (humidity, electromagnetic fields, temperature, dirt).

Robust design; minimise performance variations that is caused by variation of design sparameters, human properties and environment conditions.

Intended learning outcomes

A student who has completed the course should be able to:

• describe characteristic product properties in statistical terms

• estimate the confidence interval for the estimated reliability of a system 

• define type of probability distribution for a given amount of data

• describe aim, methodology and result of a statistical experimental design

• create a test plan for a physical and a numerical experiment,

• describe aim and procedure to carry out a Monte Carlo simulation,

• use Monte Carlo simulation to analyse how uncertainty in the model parameters influences the simulation result

• describe the aim for robust design and how the method relates to optimisation methods

• use robust design to decrease the sensitivity of the performance of a product for variations in the parameters of its components

• use robust design to decrease the sensitivity of the performance of a product for variations in the technically interactive parameters of the system

• use robust design to decrease the sensitivity of the interactive performance of a product for variations in the ergonomic parameters of the system.

Literature and preparations

Specific prerequisites

Admitted to third-cycle programmes

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

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Examination and completion

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

Grading scale

P, F

Examination

  • INL1 - Assignment, 6.0 credits, grading scale: P, 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

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 room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted

Postgraduate course

Postgraduate courses at ITM/Machine Design