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.

Analysis and Modeling of Manufacturing Systems is a set of papers on some of the newest research and applications of mathematical and computational techniques to manufacturing systems and supply chains. These papers deal with fundamental questions (how to predict factory performance: how to operate production systems) and explicitly treat the stochastic nature of failures, operation times, demand, and other important events. Analysis and Modeling of Manufacturing Systems will be of interest to readers with a strong background in operations research, including researchers and mathematically sophisticated practitioners.

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.

Flow line design is one of the major tasks in production management. The decision to install a set of machines and buffers is often highly irreversible. It determines both cost and revenue to a large extent. In order to assess the economic impact of any possible flow line design, production rates and inventory levels have to be estimated. These performance measures depend on the allocation of buffers whenever the flow of material is occasionally disrupted, for example due to machine failures or quality problems. The book describes analytical methods that can be used to evaluate flow lines much faster than with simulation techniques. Based on these fast analytical techniques, it is possible to determine a flow line design that maximizes the net present value of the flow line investment. The flow of material through the line may be non-linear, for example due to assembly operations or quality inspections.

Manufacturing systems rarely perform exactly as expected and predicted. Unexpected events, such as order changes, equipment failures and product defects, affect the performance of the system and complicate decision-making. This volume is devoted to the development of analytical methods aiming at responding to variability in a way that limits its corrupting effects on system performance. The book includes fifteen novel chapters that mostly focus on the development and analysis of performance evaluation models of manufacturing systems using decomposition-based methods, Markovian and queuing analysis, simulation, and inventory control approaches. They are organized into four distinct sections to reflect their shared viewpoints: factory design, unreliable production lines, queuing network models, production planning and assembly.

Responsible Manufacturing has become an obligation to the environment and to society itself, enforced primarily by customer perspective and governmental regulations on environmental issues. This is mainly driven by the escalating deterioration of the environment, such as diminishing raw material resources, overflowing waste sites, and increasing levels of pollution. Responsible Manufacturing related issues have found a large following in industry and academia, which aim to find solutions to the problems that arise in this newly emerged research area. Problems are widespread, including the ones related to the lifecycle of products, disassembly, material recovery, remanufacturing, and pollution prevention. Organized into sixteen chapters, this book provides a foundation for academicians and practitioners, and addresses several important issues faced by strategic, tactical, and operation planners of Responsible Manufacturing. Using efficient models in a variety of decision-making situations, it provides easy-to-use mathematical and/or simulation modeling-based solution methodologies for the majority of the issues. Features Addresses a variety of state-of-the-art issues in Responsible Manufacturing Highlights how popular industrial engineering and operations research techniques can be effectively exploited to find the most effective solutions to problems Presents how a specific issue can be approached or modeled in a given decision-making situation Covers strategic, tactical, and operational systems issues Provides a foundation for academicians and practitioners interested in building bodies of knowledge in this new and fast-growing area