Encyclopedia of Statistics in Quality and Reliability
Copyright © 1999-2014 by John Wiley and Sons, Inc. All Rights Reserved.
Online ISBN: 9780470061572
About this Book
"A must-have for everyone working on quality and reliability. It is an excellent source of information." (Technometrics)
In today’s climate of intense industrial competition, certification and qualification are increasingly important. Statistical techniques in quality engineering play a vital role in these processes.
To aid you in your work, Encyclopedia of Statistics in Quality and Reliability offers a vital knowledge source to support the development and implementation of statistical tools. It provides in-depth coverage of a wide variety of topics, including Six Sigma, Data Mining, Process Capability and Measurement Systems Analysis.
Including a large selection of case studies and practical suggestions, it appeals to professionals applying statistical methods in industry as well as to academics. Indeed, the application of statistical methods has become well established in aerospace, automotive, electronics, pharmaceutical, semiconductor and other manufacturing industries. In recent years, statistical methods have also been explored by banks, insurance companies, government agencies and healthcare organizations interested in improving the quality of their services to customers.
Edited by top experts in the field, the Encyclopedia has up-to-date information on modern statistical methods and offers a practical orientation of subjects. The Encyclopedia will provide an invaluable guide and reference for all engineers, managers and administrators responsible for improving performance within their own particular field of activity.
Encyclopedia of Statistics in Quality and Reliability covers the following:
- Management of Quality and Business Statistics
- Process Capability and Measurement Systems Analysis
- Design of Experiments and Robust Design
- Process Control
- Reliability: Life Distribution Modeling and Accelerated Testing
- Reliability: Life Cycle and Warranty Cost Prediction
- System Reliability
- Health, Safety and Environmental Applications
- Statistical and Stochastic Modeling
- Computationally Intensive Methods and Simulation
- Basic Statistics for Quality and Reliability