Stochastic Modeling And Analysis Of Manufacturing Systems
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Stochastic Modeling and Analysis of Manufacturing Systems
Author: David D. Yao
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Manufacturing systems have become increasingly complex over recent years. This volume presents a collection of chapters which reflect the recent developments of probabilistic models and methodologies that have either been motivated by manufacturing systems research or been demonstrated to have significant potential in such research. The editor has invited a number of leading experts to present detailed expositions of specific topics. These include: Jackson networks, fluid models, diffusion and strong approximations, the GSMP framework, stochastic convexity and majorization, perturbation analysis, scheduling via Brownian models, and re-entrant lines and dynamic scheduling. Each chapter has been written with graduate students in mind, and several have been used in graduate courses that teach the modeling and analysis of manufacturing systems.
Manufacturing Systems Modeling and Analysis
Author: Guy L. Curry
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-11-14
This textbook was developed to ?ll the need for an accessible but comprehensive presentation of the analytical approaches for modeling and analyzing models of manufacturing and production systems. It is an out growth of the efforts within the Industrial and Systems Engineering Department at Texas A&M to develop and teach an analytically based undergraduate course on probabilisticmodeling of m- ufacturingtype systems. The level of this textbook is directed at undergraduate and masters students in engineering and mathematical sciences. The only prerequisite for students using this textbook is a previous course covering calculus-based pr- abilityand statistics. The underlyingmethodology is queueing theory, and we shall develop the basic concepts in queueing theory in suf?cient detail that the reader need not have previously covered it. Queueing theory is a well-established dis- plinedatingback to theearly 1900’sworkof A. K. Erlang, a Danish mathematician, on telephone traf?c congestion. Although there are many textbooks on queueing theory, these texts are generally oriented to the methodological development of the ?eld and exact results and not to the practical application of using approximations in realistic modeling situations. The application of queueing theory to manufact- ing type systems started with the approximation based work of Ward Whitt in the 1980’s. His paper on QNA (a queueing network analyzer) in 1983 is the base from which most applied modeling efforts have evolved. There are several textbooks with titles similar to this book.
Handbook of Stochastic Models and Analysis of Manufacturing System Operations
Author: J. MacGregor Smith
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-05-17
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, and optimization of manufacturing systems • Facilities planning, transportation, and material handling systems analysis • Production planning, scheduling systems, management, and control • Analytical approaches to logistics and supply chain management • Integrated productivity and quality models, and their analysis • Literature surveys of issues relevant in manufacturing systems • Case studies of manufacturing system operations and analysis Today’s manufacturing system operations are becoming increasingly complex. Advanced knowledge of best practices for treating these problems is not always well known. The purpose of the book is to create a foundation for the development of stochastic models and their analysis in manufacturing system operations. Given the handbook nature of the volume, introducing basic principles, concepts, and algorithms for treating these problems and their solutions is the main intent of this handbook. Readers unfamiliar with these research areas will be able to find a research foundation for studying these problems and systems.