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# MF2024 Robust and Probabilistic Design 6.0 credits

Probabilistic design is an engineering design methodology with the aim to produce high-quality products, by systematically studying the effects of variations in the design parameters on product performance. Robust design is a methodology for optimising this quality by making the performance of the product insensitive to variations in the manufacturing, material, operational, and environmental properties.

### For course offering

Autumn 2024 Start 26 Aug 2024 programme students

### Target group

No information inserted

P1 (6.0 hp)

26 Aug 2024
27 Oct 2024

50%

Normal Daytime

English

KTH Campus

Min: 5

## Application

### For course offering

Autumn 2024 Start 26 Aug 2024 programme students

51266

## Contact

### For course offering

Autumn 2024 Start 26 Aug 2024 programme students

### Contact

Ulf Olofsson, ulfo@md.kth.se

### Examiner

No information inserted

### Course coordinator

No information inserted

### Teachers

No information inserted
Headings with content from the Course syllabus MF2024 (Spring 2020–) are denoted with an asterisk ( )

## Content and learning outcomes

### Course contents

Engineering statistics; distributions, Normal, exponetial, Weibull, confidence intervals

Design of experiments: physical and simulation experiments, suspended or censured tests

Probabilistic design; Monte-Carlo simulation (Matlab, Ansys) of performance variations caused by variations in design (manufacturing tolerances, material properies, geometric configuration), user (anthropometric data), and environmental parameters (humidity, electromagnetic fields, temperature, dust)

Robust design; minimizing performance variation due to variation in design parameters, human properties and environmental conditions

### Intended learning outcomes

After passong the course, the student should be able to:

• describe the characteristic properies of various design characteristics in statistical terms,

• assess the confidence interval of the assessed reliability of a technical system,

• find the type of probability distribution for a given set of data,

• describe the purpose for, the methodology of, and the output from Design of Experiments,

• define a testplan for a set of physical and numerical experiments,

• describe the purpose and steps for performing a Monte-Carlo simulation.

• use Monte Carlo simulations to analyse how the uncertainties in a models input variables affects the results from the model;

•  describe the purpose of Robust design and how it relates to optimization approaches,

• use the Robust design methodology to minimize the sensitivity of a technical response parameter to variations in a set of component design parameters,

• use the Robust design methodology to minimize the sensitivity of a technical response parameter to variations i a set of technical interaction parameters,

• use the Robust design methodology to minimize the sensitivity of an interactive response parameter to variations in a set of ergonomic parameters.

## Literature and preparations

### Specific prerequisites

Bachelor of Science degree in Mechanical Engineering or equivalent.

### Recommended prerequisites

No information inserted

### Equipment

No information inserted

### Literature

1 Bryan Dodson, Patrick Hammett, Rene Klerx , Probabilistic Design for Optimization and Robustness for Engineers , Wiley 2014.

2. Handouts

## Examination and completion

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

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

### Examination

• INL1 - Assignments, 3.0 credits, grading scale: P, F
• TEN1 - Written examination, 3.0 credits, grading scale: 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

### 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.

### Main field of study

Mechanical Engineering

Second cycle