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Statistical and Probabilistic Models in Reliability

  • D. C. Ionescu
  • N. Limnios

Part of the Statistics for Industry and Technology book series (SIT)

Table of contents

  1. Front Matter
    Pages i-xxxvi
  2. Statistical Methods

  3. Probabilistic Methods

    1. Front Matter
      Pages 125-125
    2. Vladimir S. Korolyuk
      Pages 127-141
    3. Vladimir S. Korolyuk, Nicolas A. Derzko, Vladimir V. Korolyuk
      Pages 143-151
    4. Krzysztof Kolowrocki
      Pages 153-183
    5. Adam Cichocki, Dorota Kurowicka, Beata Milczek
      Pages 185-197
    6. Olivier Pourret, Jérôme Collet, Jean-Louis Bon
      Pages 199-211
    7. Cristina Zahalca, Mohamed Chardi
      Pages 225-234
    8. Gheorghe Oprişan
      Pages 235-242
  4. Special Techniques and Applications

    1. Front Matter
      Pages 249-249
    2. N. Balakrishnan, P. S. Chan
      Pages 251-263
    3. Corinne Lucet, Jean-François Manouvrier
      Pages 279-294
    4. Nicolae Fota, Mohamed Kaaniche, Karama Kanoun
      Pages 321-335
    5. E. Alămoreanu, R. Iatan, R. Chiriţă, R. Ceauşu
      Pages 337-347
  5. Back Matter
    Pages 349-352

About this book

Introduction

This volume consists of twenty-four papers selected by the editors from the sixty-one papers presented at the 1st International Conference on Mathemati­ cal Methods in Reliability held at the Politehnica University of Bucharest from 16 to 19 September 1997. The papers have been divided into three sections: statistical methods, probabilistic methods, and special techniques and appli­ cations. Of course, as with any classification, some papers could be as well assigned to other sections. Problems in reliability are encountered in items in everyday usage. Relia­ bility is an important feature of household appliances, cars, telephones, power supplies, and so on, whether viewed from the vantage of the producer or the consumer. Important decisions are based on the reliability of the product. Obtaining systems that perform adequately for a specified period of time in a given environment is an important goal for both government and industry. Hence study and use of reliability theory, which can be applied in the research, development, and production phases of a system to enable the user to evaluate and improve performance, is a worthwhile venture. If reliability theory is to be useful, it must be quantitative in nature, because reliability must be demonstra­ ble. Subsequently probability and statistics, among others, play an important part in its development.

Keywords

Estimator Markov Maxima Observable Survival analysis algorithm best fit calculus classification model modeling optimization simulation statistics transformation

Editors and affiliations

  • D. C. Ionescu
    • 1
  • N. Limnios
    • 2
  1. 1.Power Engineering FacultyUniversity Politehnica BucharestBucharestRomania
  2. 2.Division Mathématiques AppliquéesUniversité de Technologie de CompiègneCompiègne CedexFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-1782-4
  • Copyright Information Springer Science+Business Media New York 1999
  • Publisher Name Birkhäuser, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-7280-9
  • Online ISBN 978-1-4612-1782-4
  • Buy this book on publisher's site