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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.
Manufacturing models - Assembly lines : reliable serial systems - Transfer lines and general serial systems - Shop scheduling with many products - Flexible manufacturing systems - Machine setup and operation sequencing - Material handling systems - Warehousing : storage and retrieval systems - General manufacturing systems : analytical queueing models - General manufacturing systems : empirical simulation models.
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.
One critical barrier leading to successful implementation of flexible manufacturing and related automated systems is the ever-increasing complexity of their modeling, analysis, simulation, and control. Research and development over the last three decades has provided new theory and graphical tools based on Petri nets and related concepts for the design of such systems. The purpose of this book is to introduce a set of Petri-net-based tools and methods to address a variety of problems associated with the design and implementation of flexible manufacturing systems (FMSs), with several implementation examples.There are three ways this book will directly benefit readers. First, the book will allow engineers and managers who are responsible for the design and implementation of modern manufacturing systems to evaluate Petri nets for applications in their work. Second, it will provide sufficient breadth and depth to allow development of Petri-net-based industrial applications. Third, it will allow the basic Petri net material to be taught to industrial practitioners, students, and academic researchers much more efficiently. This will foster further research and applications of Petri nets in aiding the successful implementation of advanced manufacturing systems.
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.
The text is designed for engineering students at the senior undergraduate level and first-year students at graduate level, and professionals (R&D engineers in the industry and factory managers). The authors offer a unique effort in presenting a unified and systematic treatment of various modeling methodologies and analysis techniques for performance evaluation of automated manufacturing systems. The text begins with an overview of automated manufacturing systems, and then provides a clear and comprehensive discussion of three principal analytical modeling paradigms: Markov Chains, Queues and Queuing Networks, and Petri Nets. Salient Features • Present the first ever treatment of the mathematical modeling of manufacturing systems. • Offers a unified study of principal analytical modeling paradigms for automated manufacturing systems. • Discusses many recent research contributions in the area of modeling of automated manufacturing systems. • Discusses many recent research contributions in the area of modeling of automated manufacturing systems, including deadlock modeling, transient analysis, queuing network approximations, Petri Net modeling, and integrated analytical modeling. • Provides a large number of exercises and problems.
Stohastic simulation; Discrete simulation; A job shop modell with material handling; Simulation software; Flexible manufacturing systems; Load-unload operations, pallets, machines; Machine buffers and central pallet storage; Operation sequences, fixtures and tools; Vehicle and movement durations; Robots, conveyors and AS/RS systems; Simulation projects; Some developments in simulation.Index.
Outlining the major issues that have to be addressed in the design and operation of each type of system, this new text explores the stochastic models of a wide range of manufacturing systems. It covers flow lines, job shops, transfer lines, flexible manufacturing systems, flexible assembly systems, cellular systems, and more. For professionals working in the area of manufacturing system modelling.
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.
The past two decades have seen a great deal of research into the stochastic modelling of production, manufacturing, and inventory systems for the purpose of improving their performance. This book provides a graduate-level introduction to these techniques covering exact, approximate, and numerical techniques. The author has aimed to strike a balance between theoretical issues and the practical aspects of modelling manufacturing systems. It is based on graduate courses given to operations research and industrial engineering students and includes numerous examples and exercises.