This book presents the mathematical models applicable to manufacturing systems management, covering problems from production to real time control. It explores manufacturing systems from the viewpoints of both physical structure and performance measures. Two broad classes of mathematical models are covered in detail: Generative models, which yield a set of decision variables optimizing a performance measure, based on mathematical optimization Evaluative models, which evaluate some performance measures as a function of some predefined decision strategy. Within this class Petri Nets and Queueing Networks are discussed. Advanced Models for Manufacturing Systems Management describes dynamic systems modeling by state equations, a unifying framework for a wide variety of models. The text/reference stresses model building, but it examines model solving as well. Computational techniques are illustrated, such as linear programming, branch and bound methods, and dynamic programming. Particular emphasis is given to the development of heuristic methods from mathematical models. The book provides readers with valuable tools for management and design. The use of descriptive models within an optimization algorithm is considered. Numerous examples illustrate theoretical concepts throughout text. Appendices are given at the end of the book in order to recall fundamentals, such as linear programming and graph theory. Appendices also appear within each chapter. In this way, readers can follow the main reading path without getting involved with details; these appendices can be read at a later time. This textual structure makes this book particularly well suited for self-study. Advanced Models for Manufacturing Systems Management is beneficial reading for both students and practitioners.

Advanced modeling techniques are a necessary tool in order to design and manage manufacturing systems effectively. This book contains a set of tutorial chapters on topics ranging from aggregate production planning to real time control, including predictive and reactive scheduling, flow management in assembly systems, simulation of robotic cells, design of manufacturing systems under uncertainty and a historical perspective on production management philosophies. The book will be of interest both to researchers and practitioners, including graduate students in Manufacturing Engineering and Operations Research.

Manufacturing systems, regardless of their size, have to work with scarce resources in dynamic environments. Effective Resource Management in Manufacturing Systems aims to provide methods for achieving effective resource allocation and to solve related problems that occur daily and often generate cost overruns. This book will be bought by postgraduate students of business, engineering and computer science as well as researchers in these fields. It will also be of interest to practitioners in manufacturing systems and operations managers in industry.

In order to compete in an increasingly demanding market, many manufacturing companies have to redesign or restructure their manufacturing systems so that a set of coherent manufacturing strategies can be supported. So this book aims to provide a comprehensive treatment of manufacturing strategy analysis (MSA) and manufacturing systems design (MSD). The strategic concerns of manufacturing are linked to subsequent manufacturing systems design activities through the use of an effective MSA/MSD interface. Topics include: A structured approach to formulating manufacturing strategies; A set of linking processes to translate MSA concerns into relevant MSD action plans; Case studies. This book is intended to help graduates and industry-based professionals to make more informed decisions when working on system-design or redesign projects.

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. In this second edition a separate appendix dealing with some of the basic event-driven simulation concepts has been added.

"This book presents relevant theoretical frameworks and most recent research findings in this area, providing significant theories for research students and scholars to carry out their continuous research as well as practitioners who aim to improve upon their understanding of distributed production planning"--

This book presents a framework and specific methods and tools for the selection and configuration of the capacity of Advanced Manufacturing Systems (AMS). AMS include Flexible Manufacturing Systems, Dedicated Manufacturing Systems, and Reconfigurable Manufacturing Systems. Starting from the characteristic of the competitive environment, the directions given by the company strategy, data regarding the products, and information regarding the different system architectures, the decision support system described here aids the decision maker by means of a formalized methodology that follows the various steps required to define the type and timing of 'capacity' acquisition and to define the detailed configuration of AMS along its life cycle. The decision making framework and tools illustrated in this volume combine decision-making theory, optimization theory, discrete event simulation and queuing networks. It will be of interest to graduate students and researchers involved in manufacturing engineering, industrial engineering and operations research.