000 04034nam a22006015i 4500
001 978-3-319-64991-7
003 DE-He213
005 20210201191432.0
007 cr nn 008mamaa
008 171115s2018 gw | s |||| 0|eng d
020 _a9783319649917
_9978-3-319-64991-7
050 4 _aQA267.7
072 7 _aGPFC
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aGPFC
_2thema
082 0 4 _a620
_223
100 1 _aKochs, Hans-Dieter.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aSystem Dependability Evaluation Including S-dependency and Uncertainty
_h[electronic resource] :
_bModel-Driven Dependability Analyses /
_cby Hans-Dieter Kochs.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXXXII, 374 p. 145 illus., 75 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
500 _aAcceso multiusuario
520 _aThe book focuses on system dependability modeling and calculation, considering the impact of s-dependency and uncertainty. The best suited approaches for practical system dependability modeling and calculation, (1) the minimal cut approach, (2) the Markov process approach, and (3) the Markov minimal cut approach as a combination of (1) and (2) are described in detail and applied to several examples. The stringently used Boolean logic during the whole development process of the approaches is the key for the combination of the approaches on a common basis. For large and complex systems, efficient approximation approaches, e.g. the probable Markov path approach, have been developed, which can take into account s-dependencies be-tween components of complex system structures. A comprehensive analysis of aleatory uncertainty (due to randomness) and epistemic uncertainty (due to lack of knowledge), and their combination, developed on the basis of basic reliability indices and evaluated with the Monte Carlo simulation method, has been carried out. The uncertainty impact on system dependability is investigated and discussed using several examples with different levels of difficulty. The applications cover a wide variety of large and complex (real-world) systems. Actual state-of-the-art definitions of terms of the IEC 60050-192:2015 standard, as well as the dependability indices, are used uniformly in all six chapters of the book.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aComputational complexity.
650 0 _aElectronic circuits.
650 0 _aQuality control.
650 0 _aReliability.
650 0 _aIndustrial safety.
650 0 _aProbabilities.
650 0 _aComputer software-Reusability.
650 1 4 _aComplexity.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T11022
650 2 4 _aCircuits and Systems.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T24068
650 2 4 _aQuality Control, Reliability, Safety and Risk.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T22032
650 2 4 _aProbability Theory and Stochastic Processes.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M27004
650 2 4 _aPerformance and Reliability.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I12077
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319649900
776 0 8 _iPrinted edition:
_z9783319649924
776 0 8 _iPrinted edition:
_z9783319879208
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-64991-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
999 _c243462
_d243461