000			03770nam a22005655i 4500
001			978-1-4471-5028-2
003			DE-He213
005			20200420220218.0
007			cr nn 008mamaa
008			130413s2013 xxk| s |||| 0|eng d
020			_a9781447150282 _9978-1-4471-5028-2
024	7		_a10.1007/978-1-4471-5028-2 _2doi
050		4	_aTA169.7
050		4	_aT55-T55.3
050		4	_aTA403.6
072		7	_aTGPR _2bicssc
072		7	_aTEC032000 _2bisacsh
082	0	4	_a658.56 _223
100	1		_aFinkelstein, Maxim. _eauthor.
245	1	0	_aStochastic Modeling for Reliability _h[electronic resource] : _bShocks, Burn-in and Heterogeneous populations / _cby Maxim Finkelstein, Ji Hwan Cha.
264		1	_aLondon : _bSpringer London : _bImprint: Springer, _c2013.
300			_aXIV, 388 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Series in Reliability Engineering, _x1614-7839
505	0		_a1.Introduction -- 2.Basic Stochastics for Reliability Analysis -- 3.Shocks and Degradation -- 4.Advanced Theory for Poisson Shock Models -- 5.Heterogeneous Populations -- 6.The basics of Burn-in -- 7.Burn-in for Repairable Systems -- 8.Burn-in for Heterogeneous Populations -- 9.Shocks as Burn-in -- 10.Stochastic Models for Environmental Stress Screening.
520			_aFocusing on shocks modeling, burn-in and heterogeneous populations, Stochastic Modeling for Reliability naturally combines these three topics in the unified stochastic framework and presents numerous practical examples that illustrate recent theoretical findings of the authors.  The populations of manufactured items in industry are usually heterogeneous. However, the conventional reliability analysis is performed under the implicit assumption of homogeneity, which can result in distortion of the corresponding reliability indices and various misconceptions. Stochastic Modeling for Reliability fills this gap and presents the basics and further developments of reliability theory for heterogeneous populations. Specifically, the authors consider burn-in as a method of elimination of 'weak' items from heterogeneous populations. The real life objects are operating in a changing environment. One of the ways to model an impact of this environment is via the external shocks occurring in accordance with some stochastic point processes. The basic theory for Poisson shock processes is developed and also shocks as a method of burn-in and of the environmental stress screening for manufactured items are considered. Stochastic Modeling for Reliability introduces and explores the concept of burn-in in heterogeneous populations and its recent development, providing a sound reference for reliability engineers, applied mathematicians, product managers and manufacturers alike.
650		0	_aEngineering.
650		0	_aStatistics.
650		0	_aIndustrial engineering.
650		0	_aProduction engineering.
650		0	_aQuality control.
650		0	_aReliability.
650		0	_aIndustrial safety.
650	1	4	_aEngineering.
650	2	4	_aQuality Control, Reliability, Safety and Risk.
650	2	4	_aIndustrial and Production Engineering.
650	2	4	_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
700	1		_aCha, Ji Hwan. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781447150275
830		0	_aSpringer Series in Reliability Engineering, _x1614-7839
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4471-5028-2
912			_aZDB-2-ENG
942			_cEBK
999			_c51706 _d51706