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.

This text presents the practical application of queueing theory results for the design and analysis of manufacturing and production systems. This textbook makes accessible to undergraduates and beginning graduates many of the seemingly esoteric results of queueing theory. In an effort to apply queueing theory to practical problems, there has been considerable research over the previous few decades in developing reasonable approximations of queueing results. This text takes full advantage of these results and indicates how to apply queueing approximations for the analysis of manufacturing systems. Support is provided through the web site http://msma.tamu.edu. Students will have access to the answers of odd numbered problems and instructors will be provided with a full solutions manual, Excel files when needed for homework, and computer programs using Mathematica that can be used to solve homework and develop additional problems or term projects.