Understanding Statistical Process Control
| Author | : | |
| Rating | : | 4.63 (827 Votes) |
| Asin | : | 0945320698 |
| Format Type | : | paperback |
| Number of Pages | : | 428 Pages |
| Publish Date | : | 2014-10-02 |
| Language | : | English |
DESCRIPTION:
This internationally acclaimed textbook is widely used for teaching basic SPC, Data Analysis, and Continual Improvement Techniques to those who work in manufacturing and process industries. While retaining the superb examples and case histories of the original, the third edition of this classic text includes new material on several important topics:An expanded definition of World Class Quality, including Excess Cost of ProductionA new Pattern Detection GuidelineNew material on how the Western Electric Zone Tests look for different sized signalsA completely new chapter on Capability, Predictability, and World Class Quality including new examples: Better ways to interpret and use the capability and performance indexes; An updated discussion of estimating the fraction nonconforming; The Myth of Long-Term Capabilityexplained and illustrated; New material on Converting Capabilities into Effective Costs of Production and Use; New exercises illustrate the power of conversion.New section on the Nature of Assignab
In short, Dr. He has the knowledge, the experience, and the ability to communicate that knowledge and experience to others. Wheeler's books and seminars, contact SPC Press at 800-545-8602. Dr. Wheeler has taught over 1000 seminars in the USA, Canada, Mexico, England, Scotland, Ireland, Wales, Norway, Sweden, Finland, Germany, Belgium, S
In short, Dr. He has worked with over 250 companies in chemical processing, health care, medical equipment, information technology, steel and aluminum production, agribusiness, food production and processing, electronics, pulp and paper processing, automotive suppliers, government agencies, and banking. Wheeler's books and seminars, contact SPC Press at 800-545-8602. Wheeler has also authored or coauthored twenty books which collectively form the definitive library for Discovery through Data Analysis.