Multivariate statistical methods in quality management /

Annotation UPGRADE 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 power...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Yang, Kai (Author)
Other Authors: Trewn, Jayant
Format: Electronic eBook
Language:Inglés
Published: New York, N.Y. : McGraw-Hill Education, [2004]
Edition:First edition.
Series:McGraw-Hill's AccessEngineering.
Subjects:
Quality control > Statistical methods.
Multivariate analysis.
Multidimensional scaling > Graphic methods.
Random variables.
Principal components analysis.
Factor analysis.
Discriminant analysis.
Cluster analysis.
Quality control.
Reliability (Engineering)
Taguchi methods (Quality control)
Critical path analysis.
Process control > Statistical methods.
Electronic books.
Online Access:Texto completo
Table of Contents:
  • Multivariate Statistical Methods and Quality
  • Overview of Multivariate Statistical Methods
  • Graphical multivariate data display and data stratification
  • Multivariate normal distribution and multivariate sampling distribution
  • Multivariate analysis of variance
  • Principal component analysis and factor analysis
  • Discriminant analysis
  • Cluster analysis
  • Mahalanobis Taguchi system (MTS)
  • Path analysis and structural model
  • Multivariate process control
  • Applications of Multivariate Statistical Methods in Business and Industry
  • Data mining
  • Chemometrics
  • Other applications
  • Overview of Quality Assurance and Possible Roles of Multivariate Statistical Methods
  • Stage 0: Impetus/ideation
  • Stage 1: Customer and business requirements study
  • Stage 2: Concept development
  • Stage 3: Product/service design/prototyping
  • Stage 4: Manufacturing process preparation/product launch
  • Stage 5: Production
  • Stage 6: Product/service consumption
  • Stage 7: Disposal
  • Overview of Six Sigma and Possible Roles of Multivariate Statistical Methods
  • Stage 1: Define the project and customer requirements (D or define step)
  • Stage 2: Measuring process performance
  • Stage 3: Analyze data and discover causes of the problem
  • Stage 4: Improve the process
  • Stage 5: Control the process
  • Graphical Multivariate Data Display and Data Stratification
  • Graphical Templates for Multivariate Data
  • Charts and graphs
  • Templates for displaying multivariate data
  • Data Visualization and Animation.

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