Skip to Content
Probabilistic Design for Optimization and Robustness for Engineers
book

Probabilistic Design for Optimization and Robustness for Engineers

by Bryan Dodson, Patrick Hammett, Rene Klerx
September 2014
Intermediate to advanced
272 pages
6h 59m
English
Wiley
Content preview from Probabilistic Design for Optimization and Robustness for Engineers

Answers to selected exercises

Chapter 2

  1. 25.05

  2. Probability (x1 < X < x2) = 0.095355

    Probability (X < x1) = 0.566184

    Probability (X < x2) = 0.661539

  3. 23.42

  4. 0.4512

  5. μ = 42.50

    σ = 40.660

  6. μ = 3.124

    σ = 1.809

  7. β = 0.571

    θ = 52.527

  8. 49.4

  9. μ = 3.125

    σ = 3.407

  10. 75.356

  11. 0.2098

  12. 315.28

  13. 1.0

  14. 0.0001515

Chapter 3

  1. 0.598
  2. 0.683
  3. 4.16
  4. 0.33
  5. μ = 100

    σ = 4.47

Chapter 4

  1. 2.43
  2. 1.31
  3. 0.27
  4. 26%
  5. μ = 100

    σ = 4.5

  6. 1.2%
  7.  

Chapter 5

    1. Nominal life: 22.05, standard deviation: 3.27
    2. Assuming normal distribution: below = 9.40%, above = 12.88%
    1. Lower power than spec: 29.8%
    2. Theoretical value: 2 400 000

      Actual value: 2 472 000

    3. Log mean parameter = 14.67

      Log STD parameter = 0.3096

    4. Below spec: 29.82%

      Above spec: 28.87%

    1. SD: 1003
    2. SD: 997
    3. Non-symmetrical distributions for input parameters have a small effect on the ability to predict the output standard deviation, usually less than 10% error on the predicted output distribution.
    1. 108
    2. 110.4
    3. SD is underestimated by 2.4.

Chapter 6

    1. 0.71
    2. 0.67
    1. 0.47
    2. The company should improve Y3 since it has the highest weightage for hitting the target and an increase in desirability would be the largest for this requirement. The new product desirability when Y3 hits the target is 0.89.
    1. 0.64
    2.  

      Requirements to be improved

          a    Strength of material ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

Read now

Unlock full access

More than 5,000 organizations count on O’Reilly

AirBnbBlueOriginElectronic ArtsHomeDepotNasdaqRakutenTata Consultancy Services

QuotationMarkO’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.
Julian F.
Head of Cybersecurity
QuotationMarkI wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.
Addison B.
Field Engineer
QuotationMarkI’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.
Amir M.
Data Platform Tech Lead
QuotationMarkI'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Mark W.
Embedded Software Engineer

You might also like

Optimization for Engineering Problems

Optimization for Engineering Problems

Kaushik Kumar, J. Paulo Davim
Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

Jaroslaw Sobieszczanski-Sobieski, Alan Morris, Michel van Tooren
Multimodal Scene Understanding

Multimodal Scene Understanding

Michael Ying Yang, Bodo Rosenhahn, Vittorio Murino

Publisher Resources

ISBN: 9781118796306Purchase book