Multivariate Statistical Methods in Quality Management
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Multivariate Statistical Methods in Quality Management by Kai Yang
Book DescriptionUpgrade manufacturing and service performance with powerful statistical tools. There's no better way to master the most rigorous statistical methods available for analyzing the performance of complex systems - "Multivariate Statistical Methods in Quality Management" teaches powerful analytic tools for troubleshooting, root cause analysis, process control, quality improvement, and many other applications.Written by statistics experts who specialize in reliability and quality engineering, this unique resource introduces the fundamentals and then demonstrates how to: choose the best method for each data set; make complex data intelligible with graphical tools; coax important hidden information from data with graphical 3-D software and numerical multivariate data stratification; perform data reduction with principal component analysis, factor analysis, and discriminant analysis; apply multivariate methods in Six Sigma enterprises; get clarification from case studies, models, and 50 illustrations; and, uncover the source of problems and pinpoint solutions in arenas from manufacturing processes to sales performance and beyond.
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Book DetailsISBN: 9780071432085
(231mm x 157mm x 27mm)
Imprint: McGraw-Hill Professional
Publisher: McGraw-Hill Education - Europe
Publish Date: 1-Mar-2004
Country of Publication: United States
Books By Author Kai Yang
Design for Six Sigma, Hardback (September 2008)
An update of the leading resource for industrial engineers and Six Sigma black belts who want to start a Design for Six Sigma program.
Voice of the Customer, Hardback (December 2007)» View all books by Kai Yang
Demonstrates how Design for Six Sigma's statistical methods can be deployed to identify key customer needs and assess the cost of poor quality, design robust product to meet those needs, optimize product life cycles, and accurately validate their findings.
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Author Biography - Kai Yang
Kai Yang, Ph.D., has consulted extensively in many areas of quality and reliability engineering. He is Associate Professor of Industrial and Manufacturing Engineering at Wayne State University, Detroit, Michigan. He lives in West Bloomfield, Michigan. Jayant Trewn, Ph.D., is a research faculty member at Beaumont Hospital in Royal Oak, Michigan. He is responsible for implementing cutting edge industrial engineering tools in hospital and health care management. Dr. Trewn was a Director of Quality and Productivity Improvement at Vetri Systems, a Lason Company. He was responsible for business process design and improvement in the global business environment.
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