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Handbook of Stochastic Models and Analysis of Manufacturing System Operations.

This handbook surveys important stochastic problems and models in manufacturing system operations and their stochastic analysis. Using analytical models to design and control manufacturing systems and their operations entail critical stochastic performance analysis as well as integrated optimization...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Smith, J. M. (J. MacGregor)
Otros Autores: Tan, B. (Barış)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Dordrecht : Springer, 2013.
Colección:International series in operations research & management science.
Temas:
Acceso en línea:Texto completo

MARC

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245 1 0 |a Handbook of Stochastic Models and Analysis of Manufacturing System Operations. 
260 |a Dordrecht :  |b Springer,  |c 2013. 
300 |a 1 online resource (396 pages). 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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490 1 |a International Series in Operations Research & Management Science ;  |v v. 192 
505 0 |a Preface; Contents; Contributors; Chapter1 The Design of Manufacturing Systems to Cope with Variability; 1.1 Introduction; 1.2 Manufacturing Needs Dedicated Problem Solvers; 1.3 Manufacturing Systems; 1.3.1 Job Shops; 1.3.1.1 Scheduling Job Shops; 1.3.2 Flow Lines; 1.3.2.1 Quality Problems in Moving Belt Flow Lines; 1.3.2.2 Inventory with Unpaced Systems; 1.3.2.3 Inspection and Repair; 1.4 Improving on the Job Shop and the Flow Line; 1.4.1 Flexible Manufacturing Systems (FMS); 1.4.2 Central Storage and Dispatch; 1.4.3 Cells and Teams; 1.5 Conclusions; References. 
505 8 |a Chapter2 Modeling Automated Warehouses Using Semi-Open Queueing Networks2.1 Introduction; 2.2 SOQN Notation; 2.3 Single-Class SOQN with Two Stages of Exponential Serversand Poisson Arrivals; 2.3.1 State Space Solution; 2.3.2 Matrix Geometric Method Solution; 2.3.3 Numerical Example 1; 2.4 Single-Class SOQN with Multiple Stages of Exponential Servers and Poisson Arrivals; 2.4.1 Decomposition-Aggregation Method; 2.4.2 Numerical Example 2; 2.5 Phase-Type Distribution; 2.5.1 Definition; 2.5.2 Closure Properties and Kronecker Product; 2.5.2.1 Closure Properties; 2.5.2.2 Kronecker Product. 
505 8 |a 2.6 Single-Class SOQN with Two Stages of General Servers and General Arrival2.6.1 State Space Analysis; 2.6.2 Numerical Example 3; 2.6.3 Multiple Servers; 2.6.4 Numerical Example 4; 2.7 Single-Class SOQN with Multiple Stages of General Servers and General Arrival; 2.7.1 Modified Decomposition-Aggregation Method; 2.7.2 Numerical Example 5; 2.8 Multi-Class SOQN with Multiple Stages of General Serversand General Arrivals; 2.8.1 Aggregation Method; 2.8.2 Numerical Example 6; 2.9 Conclusions; References. 
505 8 |a Chapter3 Exact Analysis of Discrete Part Production Lines: The Markovian Queueing Network and the Stochastic Automata Networks Formalisms3.1 Introduction and Literature Review; 3.2 The Markovian Formalism; 3.2.1 The Algorithm for the Generation of the Conservative Matrix A for K-Station Reliable Exponential Production Lines with Inter-station Buffers; 3.2.1.1 Number of States; 3.2.1.2 Ordering of States; 3.2.1.3 Structure of Matrix A; 3.2.2 The Queueing Network Model of a Three-Station Reliable Exponential Production Line; 3.3 The Stochastic Automata Networks Formalism (SAN). 
505 8 |a 3.3.1 Definitions and Properties of Classical Tensor Algebra (CTA) and Generalized Tensor Algebra (GTA)3.3.1.1 Definitions and Properties of Classical Tensor Algebra (CTA); 3.3.1.2 Definitions and Properties of Generalized Tensor Algebra (GTA); 3.3.2 Definition of Kronecker Descriptors Using Tensor Algebra; 3.3.3 The Equivalent SAN Model to the Queueing Network Model of the Three-Station Line; 3.3.3.1 Tensor Representation of the Three-Station Example in SAN; 3.4 Software Tools and Results; 3.4.1 Numerical Results; 3.5 Conclusions; References. 
500 |a Chapter4 Models of Leveling for Lean Manufacturing Systems. 
520 |a This handbook surveys important stochastic problems and models in manufacturing system operations and their stochastic analysis. Using analytical models to design and control manufacturing systems and their operations entail critical stochastic performance analysis as well as integrated optimization models of these systems. Topics deal with the areas of facilities planning, transportation, and material handling systems, logistics and supply chain management, and integrated productivity and quality models covering: Stochastic modeling and analysis of manufacturing systems Design, analysis, an. 
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650 0 |a Business. 
650 0 |a Production management. 
650 0 |a Operations research. 
650 0 |a Decision making. 
650 0 |a Management science. 
650 2 |a Operations Research 
650 2 |a Decision Making 
650 4 |a Manufacturing processes  |x Mathematical models  |v Handbooks, manuals, etc. 
650 4 |a Operations research. 
650 4 |a Stochastic models  |v Handbooks, manuals, etc. 
650 6 |a Affaires. 
650 6 |a Production  |x Gestion. 
650 6 |a Recherche opérationnelle. 
650 6 |a Prise de décision. 
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830 0 |a International series in operations research & management science. 
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