000 04188nam a22004815i 4500
001 u372798
003 SIRSI
005 20160812084115.0
007 cr nn 008mamaa
008 100422s2010 xxk| s |||| 0|eng d
020 _a9781849960007
_9978-1-84996-000-7
040 _cMX-MeUAM
050 4 _aTA177.4-185
082 0 4 _a658.5
_223
100 1 _aAllen, Theodore T.
_eauthor.
245 1 0 _aIntroduction to Engineering Statistics and Lean Sigma
_h[recurso electrónico] :
_bStatistical Quality Control and Design of Experiments and Systems /
_cby Theodore T. Allen.
250 _aSecond Edition.
264 1 _aLondon :
_bSpringer London,
_c2010.
300 _aXXIII, 572 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aStatistical Quality Control -- Statistical 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 -- Design for Six Sigma -- Lean Sigma Project Design.
520 _aLean production, has long been regarded as critical to business success in many industries. Over the last ten years, instruction in six sigma has been increasingly linked with learning about the elements of lean production. Introduction to Engineering Statistics and Lean Sigma builds on the success of its first edition (Introduction to Engineering Statistics and Six Sigma) to reflect the growing importance of the "lean sigma" hybrid. As well as providing detailed definitions and case studies of all six sigma methods, Introduction to Engineering Statistics and Lean Sigma forms one of few sources on the relationship between operations research techniques and lean sigma. Readers will be given the information necessary to determine which sigma methods to apply in which situation, and to predict why and when a particular method may not be effective. Methods covered include: • control charts and advanced control charts, • failure mode and effects analysis, • Taguchi methods, • gauge R&R, and • genetic algorithms. The second edition also greatly expands the discussion of Design For Six Sigma (DFSS), which is critical for many organizations that seek to deliver desirable products that work first time. It incorporates recently emerging formulations of DFSS from industry leaders and offers more introductory material on the design of experiments, and on two level and full factorial experiments, to help improve student intuition-building and retention. The emphasis on lean production, combined with recent methods relating to Design for Six Sigma (DFSS), makes Introduction to Engineering Statistics and Lean Sigma a practical, up-to-date resource for advanced students, educators, and practitioners.
650 0 _aEngineering.
650 0 _aEconomics
_xStatistics.
650 0 _aEngineering economy.
650 0 _aBusiness planning.
650 1 4 _aEngineering.
650 2 4 _aEngineering Economics, Organization, Logistics, Marketing.
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
650 2 4 _aOperations Research/Decision Theory.
650 2 4 _aOrganization/Planning.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781848829992
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-1-84996-000-7
596 _a19
942 _cLIBRO_ELEC
999 _c200678
_d200678