Practical Statistical Tools for the Reliability Engineer

✍ Scribed by Coppola A.

• Tongue: English
• Leaves: 121
• Category: Library

✦ Synopsis

Prepared by Reliability Analysis Center under contact to Defense Supply Center Columbus.
September 1999, 121 p.

This report provides basic instruction in statistics and its applications to reliability engineering. General probability and statistical concepts are explained and specific statistical tools are introduced by considering their applications to measuring reliability, demonstrating reliability, reliability growth testing, sampling, statistical quality control, and process improvement.
Statistical tools are powerful aids to reliability engineering and related disciplines. However, many people, including engineers, consider the process of mastering statistics to be painful. This book is an attempt to provide the reliability practitioner a reasonable capability in the use of statistical tools without the pain. For this reason, discussion of statistical theory will be kept to a minimum, and useful tools will be demonstrated by showing their practical application to various reliability engineering tasks.

Table Of Contents
What You Need To Know About Probability
When Events are Independent
When Events are Mutually Exclusive
When Events are Not Independent
In Summary
Introduction To Statistics
Many Ways to be "Average"
Ways to Measure Spread
Introduction to Distributions
Testing Hypotheses
For Further Study
Some Distributions And Their Uses
Discrete Distributions
Continuous Distributions
In Summary
Measuring Reliability
General Principles
The Versatile Weibull Distribution
Measuring Reliability of Repairable Systems
Measuring Reliability of "One-Shot" Products
Demonstrating Reliability
Zero Failure Tests
Tests Allowing Failures
Testing Under the Exponential Distribution
Other Test Considerations
Reliability Growth Testing
Duane Growth Analysis
AMSAA Growth Analysis
Sampling (Polling) And Statistical Quality Control
Measuring Quality from Samples
Demonstrating Acceptability Through Sampling
Statistical Quality Control
Using Statistics To Improve Processes
Designing Experiments
Is There Really a Difference?
How Strong is the Correlation?
Closing Comments
Appendix. Poisson Probabilities
Appendix. Cumulative Poisson Probabilities
Appendix. The Standard Normal Distribution
Appendix. The Chi-Square Distribution
Appendix. The Student t Distribution
Appendix. Critical Values of the F Distribution for Tests of Significance

✦ Subjects

Машиностроение и материалообработка;Теория надежности