Synopses & Reviews
To practice engineering effectively, engineers must need to have a working knowledge of statistical concepts and methods. What they do not need is a background heavy on statistical theory and number crunching.
Statistical Methods for Industrial Process Control provides the practical statistics foundation engineers can immediately apply to the work they do every day, regardless of their industry or specialty. The author illustrates statistical concepts and methods with authentic semiconductor manufacturing process examples-integrated circuit fabrication is an exceedingly rich medium for communicating statistical concepts. However, once learned, these concepts and methods can easily be extended and applied to a variety of other industries.
The text emphasizes the application of statistical tools, rather than statistical theory. Modern advances in statistical software have made tedious computations and formula memorization unnecessary. Therefore, the author demonstrates software use throughout the book and supplies MINITAB examples and SAS programs. Review problems at the end of each chapter challenge and deepen readers' understanding of the material.
Statistical Methods for Industrial Process Control addresses topics that support the work engineers do, rather than educate them as statisticians, and these topics also reflect modern usage. It effectively introduces novice engineers to a fascinating industry and enables experienced engineers to build upon their existing knowledge and learn new skills.
Synopsis
This combined text and reference is the second in the "Solid State Science and Engineering" series and is designed to teach semiconductor engineers to apply sophisticated statistical methods to problems of semiconductor manufacture and fabrication.
Synopsis
Emphasizing the practical application of statistical tools, this outstanding volume gives engineers and students a solid introduction to the sophisticated techniques used in semiconductor manufacture and fabrication. Throughout the book, examples are taken from the semiconductor industry, but the techniques covered can be readily applied to many other industrial processes. Statistical Methods for Industrial Process Control begins with coverage of essential statistical concepts, including causal relationships and application of knowledge about patterns or variation to designing sample schemes. This material provides the basis for understanding the material on ensuring that measuring equipment is capable of measuring important parameters with the requisite precision, accuracy and stability. With this foundation, the book teaches readers the statistical process control methods needed to stabilize the process. Although written with a specific focus on the semiconductor industry, Statistical Methods for Industrial Process Control will have much wider appeal. The statistical concepts can be readily applied by engineers in other process industries, including chemistry, manufacturing, and pharmaceuticals. In addition, the clear presentation, wide use of examples, review problems and abundant references make this valuable for advanced statistics and engineering students.
Description
Includes bibliographical references (p. 413-416) and index.