B. K. JONES, "Logarithmic distributions in reliability analysis", Microelectronics Reliability, Volume 42, Issues 4-5, April-May 2002, pp. 779-786.

B. K. JONES, "Logarithmic distributions in reliability analysis", Microelectronics Reliability, Volume 42, Issues 4-5, April-May 2002, pp. 779-786. Copyright - [Précédente] [Première page] [Suivante] - Home

Article : [ART234]

Titre : B. K. JONES, Logarithmic distributions in reliability analysis, Microelectronics Reliability, Volume 42, Issues 4-5, April-May 2002, pp. 779-786.

Cité dans :[REVUE296] Elsevier Science, Microelectronics Reliability, Volume 42, Issues 4-5, Pages 463-804, April - May 2002.
Cité dans : [DIV334]  Recherche sur les mots clés power cycling of power device, mai 2002.

Auteur : B. K. Jones

Vers : Bibliographie
Adresse : Department of Physics, School of Physics and Chemistry, Lancaster University, Lancaster LA1 4YB, UK
Tel. : +44-1524-593657
Fax. : +44-1524-844037
Lien : mailto:b.jones@lancaster.ac.uk
Source : Microelectronics Reliability
Volume : 42
Isues : 4-5
Date : April-May 2002
Pages : 779 - 786
DOI : 10.1016/S0026-2714(02)00031-8
PII : S0026-2714(02)00031-8
Lien : private/JONES1.pdf - 8 pages, 131 Ko.
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Abstract :
Real-life systems are complex, with many independent parameters which can affect
the system. Their behaviour can therefore be very variable. This is especially
true of the more involved processes which occur in reliability and degradation
processes. However, there are some characteristics which are observed which can
be understood simply because they are characteristic of complex systems. These
include distributions that are very often logarithmic rather than uniform,
log-normal failure distributions and 1/f noise. A wide variety of diverse
examples is given to illustrate the common occurrence of such observations
together with the underlying unifying themes. There are several basic reasons
for the origin of logarithmic distributions. One is that they arise from
multiplicative processes. Another is that although basic science is often
introduced as linear, with non-linear effects added as a correction, complex
systems are often inherently non-linear. This produces multiplicative effects,
such as harmonic generation and fractal behaviour.

Article Outline
1. Introduction
2. Pareto and Zipf
3. Scale invariance
4. Benford
5. 1/f noise
6. Log-normal distributions
7. Conclusions

Bibliographie

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