This volume contains extended versions of 28 carefully selected and reviewed papers presented at The Fourth International Conference on Mathematical Methods in Reliability in Santa Fe, New Mexico, June 21β25, 2004, the leading conference in reliability research. The meeting serves as a forum for dis
Statistical Reliability Engineering
β Scribed by Boris Gnedenko, Igor Pavlov, Igor Ushakov(auth.)
- Year
- 1999
- Tongue
- English
- Leaves
- 509
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Proven statistical reliability analysis methods-available for the first time to engineers in the West While probabilistic methods of system reliability analysis have reached an unparalleled degree of refinement, Russian engineers have concentrated on developing more advanced statistical methods. Over the past several decades, their efforts have yielded highly evolved statistical models that have proven to be especially valuable in the estimation of reliability based upon tests of individual units of systems. Now Statistical Reliability Engineering affords engineers a unique opportunity to learn both the theory behind and applications of those statistical methods. Written by three leading innovators in the field, Statistical Reliability Engineering:
* Covers all mathematical models for statistical reliability analysis, including Bayesian estimation, accelerated testing, and Monte Carlo simulation
* Focuses on the estimation of various measures of system reliability based on the testing of individual units
* Contains new theoretical results available for the first time in print
* Features numerous examples demonstrating practical applications of the theory presented
Statistical Reliability Engineering is an important professional resource for reliability and design engineers, especially those in the telecommunications and electronics industries. It is also an excellent course text for advanced courses in reliability engineering.Content:
Chapter 1 Main Knowledge of Statistics (pages 1β59):
Chapter 2 Plans of Tests with a Single Censorship (pages 60β99):
Chapter 3 Censored Samples (pages 100β144):
Chapter 4 Bayes Methods of Reliability Estimation (pages 145β156):
Chapter 5 Accelerated Testing (pages 157β177):
Chapter 6 Testing with No Failures (pages 179β207):
Chapter 7 System Confidence Limits Based on Unit Test Results (pages 208β281):
Chapter 8 Confidence Limits for Systems Consisting of Units with Exponential Distribution of Time to Failure (pages 282β327):
Chapter 9 Sequential Criteria of Hypothesis Testing and Confidence Limits for Reliability Indices (pages 328β403):
Chapter 10 Monte Carlo Simulation (pages 404β424):
Chapter 11 Monte Carlo Simulation for Optimal Redundancy (pages 425β452):
π SIMILAR VOLUMES
<p><span>This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the authorβs recent research and publications as
<p><span>This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the authorβs recent research and publications as
<p><span>This book is a convenient and comprehensive guide to statistics. A resource for quality technicians and engineers in any industry, this second edition provides even more equations and examples for the readerβwith a continued focus on algebra-based math. Those preparing for ASQ certification