Fracture Mechanics 1

Analysis of Reliability and Quality Control
1. Auflage 2012
ISBN: 978-1-84821-440-8
Verlag: Wiley

Buch, Englisch, 272 Seiten, Format (B × H): 160 mm x 236 mm, Gewicht: 590 g

This first book of a 3-volume set on Fracture Mechanics is mainly centered on the vast range of the laws of statistical distributions encountered in various scientific and technical fields. These laws are indispensable in understanding the probability behavior of components and mechanical structures that are exploited in the other volumes of this series, which are dedicated to reliability and quality control.
The author presents not only the laws of distribution of various models but also the tests of adequacy suited to confirm or counter the hypothesis of the law in question, namely the Pearson (x2) test, the Kolmogorov-Smirnov (KS) test, along with many other relevant tests.
This book distinguishes itself from other works in the field through its originality in presenting an educational approach which aims at helping practitioners both in academia and industry. It is intended for technicians, engineers, designers, students, and teachers working in the fields of engineering and vocational education. The main objective of the author is to provide an assessment of indicators of quality and reliability to aid in decision-making. To this end, an intuitive and practical approach, based on mathematical rigor, is recommended.

Autoren/Hrsg.

Grous, Ammar

Inhaltsverzeichnis

Preface ix

Chapter 1. Elements of Analysis of Reliability and Quality Control 1

1.1. Introduction 1

1.1.1. The importance of true physical acceleration life models (accelerated tests = true acceleration or acceleration) 3

1.1.2. Expression for linear acceleration relationships 4

1.2. Fundamental expression of the calculation of reliability 5

1.3. Continuous uniform distribution 9

1.3.1. Distribution function of probabilities (density of probability) 10

1.3.2. Distribution function 10

1.4. Discrete uniform distribution (discrete U) 12

1.5. Triangular distribution 13

1.5.1. Discrete triangular distribution version 13

1.5.2. Continuous triangular law version 14

1.5.3. Links with uniform distribution 14

1.6. Beta distribution 15

1.6.1. Function of probability density 16

1.6.2. Distribution function of cumulative probability 18

1.6.3. Estimation of the parameters (p, q) of the beta distribution 19

1.6.4. Distribution associated with beta distribution 20

1.7. Normal distribution 20

1.7.1. Arithmetic mean 20

1.7.2. Reliability 22

1.7.3. Stabilization and normalization of variance error 23

1.8. Log-normal distribution (Galton) 28

1.9. The Gumbel distribution 28

1.9.1. Random variable according to the Gumbel distribution (CRV, E1 Maximum) 29

1.9.2. Random variable according to the Gumbel distribution (CRV E1 Minimum) 30

1.10. The Frechet distribution (E2 Max) 31

1.11. The Weibull distribution (with three parameters) 32

1.12. The Weibull distribution (with two parameters) 35

1.12.1. Description and common formulae for the Weibull distribution and its derivatives 37

1.12.2. Areas where the extreme value distribution model can be used 39

1.12.3. Risk model 40

1.12.4. Products of damage 41

1.13. The Birnbaum–Saunders distribution 42

1.13.1. Derivation and use of the

Über Autor(innen)

Ammar Grous is Teacher of Mechanical Engineering at CéGEP de l'Outaouais (Academic College), Gatineau, Quebec, Canada.