Introduction to Engineering Statistics and Six Sigma : Statistical Quality Control and Design of Experiments and Systems /
By: Allen, Theodore T [author.].
Contributor(s): SpringerLink (Online service).
Material type:
BookPublisher: London : Springer London, 2006.Edition: 2.Description: XXII, 530 p. 114 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781846282003.Subject(s): Engineering | Organization | Planning | Operations research | Decision making | Statistics | Computational intelligence | Engineering economics | Engineering economy | Engineering | Engineering Economics, Organization, Logistics, Marketing | Computational Intelligence | Operation Research/Decision Theory | Organization | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences | Statistics for Business/Economics/Mathematical Finance/InsuranceDDC classification: 658.5 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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E books
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PK Kelkar Library, IIT Kanpur | Available | EBK8921 |
Statistical Quality Control -- Quality Control and Six Sigma -- Define Phase and Strategy -- Measure Phase and Statistical Charting -- Analyze Phase -- Improve or Design Phase -- Control or Verify Phase -- Advanced SQC Methods -- SQC Case Studies -- SQC Theory -- Design of Experiments (DOE) and Regression -- DOE: The Jewel of Quality Engineering -- DOE: Screening Using Fractional Factorials -- DOE: Response Surface Methods -- DOE: Robust Design -- Regression -- Advanced Regression and Alternatives -- DOE and Regression Case Studies -- DOE and Regression Theory -- Optimization and Strategy -- Optimization and Strategy -- Tolerance Design -- Six Sigma Project Design.
Many have heard that six sigma methods are necessary to survive, let alone thrive, in today’s competitive markets, but are not really sure what the methods are or how or when to use them. Introduction to Engineering Statistics and Six Sigma contains precise descriptions of all of the many related methods and details case studies showing how they have been applied in engineering and business to achieve millions of dollars of savings. Specifically, the methods introduced include many kinds of design of experiments (DOE) and statistical process control (SPC) charting approaches, failure mode and effects analysis (FMEA), formal optimization, genetic algorithms, gauge reproducibility and repeatability (R&R), linear regression, neural nets, simulation, quality function deployment (QFD) and Taguchi methods. A major goal of the book is to help the reader to determine exactly which methods to apply in which situation and to predict how and when the methods might not be effective. Illustrative examples are provided for all the methods presented and exercises based on case studies help the reader build associations between techniques and industrial problems. A glossary of acronyms provides familiarity with six sigma terminology and solutions to homework and practice exams are included.
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