This is a survey of new statistical and probabilistic models for reliability analysis and applications in science, engineering and technology. It provides broad coverage of new models and methods such as accelerated tests, stress reliability, petri nets, and asymptotic reliability. Editor(s): Limnios, Nikolaos; Ionescu, Dumitru Cezar. Series: Statistics for Industry and Technology. Num Pages: 388 pages, biography. BIC Classification: TBJ. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 254 x 178 x 22. Weight in Grams: 902. . 1998. Hardback. . . . .

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Bibliographic Details

Title: Statistical and Probabilistic Models in Reliability
Publisher: Birkhauser Boston Inc
Publication Date: 1998
Language: English
ISBN 10: 0817640681
ISBN 13: 9780817640682
Binding: Hardcover
Condition: New

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Synopsis

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.

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