
- 768 pages
- English
- PDF
- Available on iOS & Android
Introduction to Statistical Quality Control
About this book
Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.
Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences.
A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, provides students with a solid base of conceptual and practical knowledge.
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Information
Table of contents
- Cover
- Title Page
- Copyright
- About the Author
- Preface
- Contents
- Part 1 Introduction
- Part 2 Statistical Methods Useful in Quality Control and Improvement
- Part 3 Basic Methods of Statistical Process Control and Capability Analysis
- Part 4 Other Statistical Process-Monitoring and Control Techniques
- Part 5 Process Design and Improvement with Designed Experiments
- Part 6 Acceptance Sampling
- Appendix
- Bibliography
- Index
- EULA