This book equips the reader with a compact information source on all the most recent methodological tools available in the area of reliability prediction and analysis.
Topics covered include reliability mathematics, organisation and analysis of data, reliability modelling and system reliability evaluation techniques. Environmental factors and stresses are taken into account in computing the reliability of the involved components. The limitations of models, methods, procedures, algorithms and programmes are outlined. The treatment of maintained systems is designed to aid the worker in analysing systems with more realistic and practical assumptions. Fault tree analysis is also extensively discussed, incorporating recent developments. Examples and illustrations support the reader in the solving of problems in his own area of research. The chapters provide a logical and graded presentation of the subject matter bearing in mind the difficulties of a beginner, whilst bridging the information gap for the more experienced reader. The work will be of considerable interest to engineers working in various industries, research organizations, particularly in defence, nuclear, chemical, space or communications. It will also be an indispensable study aid for serious-minded students and teachers.
1. Reliability Engineering: An overview. Historical development. Reliability: A birth-to-death problem. Reliability: An interdisciplinary effort. Reliability education and research. Problems of developing countries. Reliability prediction and analysis. Problems in prediction and analysis. Challenges for future. Scope of the book. 2. Reliability Mathematics. Classical set theory. Boolean algebra. Sample space. Definitions of probability. Basic properties of probability. Independent events. Conditional probability. Multiplication theorem. Total probability theorem. Bayes' theorem. Random variables. Probability distributions. Cumulative distributions. Mathematical expectation. Variance. Covariance and correlation. Moments. Moment generating functions. Probability distributions. Joint probability distributions. Distributions of several random variables. Some useful limit theorems. Estimation theory. Laplace transform. Markov processes. Random number generation. 3. Reliability Data Analysis and Management. The reliability function. Mean time to failure. Variance. The bathtub curve. Linear hazard models. Other hazard models. Analysis of failure data. Probability graph papers. Illustrations. Hazard function plots. Selection of a distribution. Statistical estimation of failure data. Interval estimates. Reliability data management. 4. Reliability Prediction from Stress-Strength Models. Stresses due to internal and external environments. Physics of failures. Reliability from stress-strength distributions. Reliability from similar stress-strength distributions. Reliability from dissimilar stress-strength distributions. Graphical approach. Time dependent stress-strength models. Environmental factors. Environmental testing; Test specifications. Stress derating. Estimation of part failure rate. 5. System Reliability Modelling. System modelling. Assumptions for modelling. Two state modelling. Thre
- © Elsevier Science 1992
- 2nd June 1992
- Elsevier Science
- eBook ISBN:
- Hardcover ISBN:
@qu:...the coverage is the most comprehensive of any book yet written...it covers every aspect of reliability in the widest possible field. @source:Microelectronics and Reliability @qu:... the book of K.B. Misra who is an internationally leading specialist in reliability engineering, is an outstanding and up to now surely the most comprehensive text on the subject, and will find numerous satisfied readers. @source:Optimization @qu:It should be on every engineer's bookshelf. @source:Current Science @qu:... this book is an authentic and outstanding piece of work of high utilitarian value and constitutes a most comprehensive state-of-art text book in the field of Reliability Analysis in the decade of 1990's. @source:International Journal of General Systems