Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook.
The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data.
SMRD2 features:
Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.
頁數:700
版次:第2版
年份:2022年
規格:精裝/單色
ISBN:9781118115459
1 Reliability Concepts and an Introduction to Reliability Data
2 Models, Censoring, and Likelihood for Failure-Time Data
3 Nonparametric Estimation for Failure-Time Data
4 Some Parametric Distributions Used in Reliability Applications
5 System Reliability Concepts and Methods
6 Probability Plotting
7 Parametric Likelihood Fitting Concepts: Exponential Distribution
8 Maximum Likelihood Estimation for Log-Location-Scale Distributions
9 Parametric Bootstrap and Other Simulation-Based Confidence Interval Methods
10 An Introduction to Bayesian Statistical Methods for Reliability
11 Special Parametric Models
12 Comparing Failure-Time Distributions
13 Planning Life Tests for Estimation
14 Planning Reliability Demonstration Tests
15 Prediction of Failure Times and the Number of Future Field Failures
16 Analysis of Data with More than One Failure Mode
17 Failure-Time Regression Analysis
18 Analysis of Accelerated Life Test Data
19 More Topics on Accelerated Life Testing
20 Degradation Modeling and Destructive Degradation Data Analysis
21 Repeated-Measures Degradation Modeling and Analysis
22 Analysis of Repairable System and Other Recurrent Events Data
23 Case Studies and Further Applications