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001			291455
003			MX-SnUAN
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007			cr nn 008mamaa
008			150903s2006 xxk| o |||| 0|eng d
020			_a9781846282003 _99781846282003
024	7		_a10.1007/1846282004 _2doi
035			_avtls000343726
039		9	_a201509030750 _bVLOAD _c201404120954 _dVLOAD _c201404090732 _dVLOAD _y201402061203 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTA177.4-185
100	1		_aAllen, Theodore T. _eautor _9306060
245	1	0	_aIntroduction to Engineering Statistics and Six Sigma : _bStatistical Quality Control and Design of Experiments and Systems / _cby Theodore T. Allen.
250			_a2.
264		1	_aLondon : _bSpringer London, _c2006.
300			_axxii, 529 páginas 114 ilustraciones _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aStatistical 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.
520			_aMany 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.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781852339555
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/1-84628-200-4 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c291455 _d291455