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001			95717
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005			20230102112718.0
006			m o d
007			cr cnu|||unuuu
008			170403s2017 sz a ob 000 0 eng d
020			_a3319533215 _q(electronic bk.)
020			_a9783319533216 _q(electronic bk.)
020			_z3319533207
020			_z9783319533209
040			_aN$T _cN$T _dN$T _dEBLCP _dYDX _dGW5XE _dNJR _dIOG _dOCLCF _dAZU _dUPM _dUAB _dMERER _dESU _dOCLCQ _dJBG _dIAD _dICN _dILO _dVT2 _dOTZ _dOCLCQ _dU3W _dES-MaUEC _bspa
050		4	_aTA347.N46 _bM683 2017 EB
100	1		_aMota, Idalia Flores de la, _eautor
245	1	0	_aRobust modelling and simulation : _bintegration of SIMIO with coloured Petri nets _cIdalia Flores De La Mota [and 3 others].
264		1	_aCham, Switzerland _bSpringer _c2017.
300			_a1 recurso en línea _bilustraciones
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
500			_aSpringerLink _bSpringer Engineering eBooks 2017 English+International
504			_aIncluye referencias bibliográficas
505	0		_aPreface -- Introduction -- Chapter 1: Introduction to Digital Simulation.-Chapter 2: Statistics elements for simulation -- Chapter 3: Modelling of Systems using Petri Nets -- Chapter 4: Integrating Coloured Petri Nets with SIMIO -- Chapter 5: Modelling Example -- References -- Annex.
520	3		_aThis book presents for the first time a methodology that combines the power of a modelling formalism such as colored petri nets with the flexibility of a discrete event program such as SIMIO. Industrial practitioners have seen the growth of simulation as a methodology for tacking problems in which variability is the common denominator. Practically all industrial systems, from manufacturing to aviation are considered stochastic systems. Different modelling techniques have been developed as well as mathematical techniques for formalizing the cause-effect relationships in industrial and complex systems. The methodology in this book illustrates how complexity in modelling can be tackled by the use of coloured petri nets, while at the same time the variability present in systems is integrated in a robust fashion. The book can be used as a concise guide for developing robust models, which are able to efficiently simulate the cause-effect relationships present in complex industrial systems without losing the simulation power of discrete-event simulation. In addition SIMIO's capabilities allows integration of features that are becoming more and more important for the success of projects such as animation, virtual reality, and geographical information systems (GIS).
650		7	_aIngeniería civil _2embne _0(OCoLC)fst01059237 _0 _9138928
700	1		_aGuasch, Antoni.
700	1		_aMujica Mota, Miguel.
700	1		_aPiera, M. A. _q(Miquel Angel)
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-319-53321-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017C
998			_b02/2018 _dz _e- _zSI
999			_c95717 _d95717 _x1