J. MacGregor Smith – författare

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.

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 textbook provides an introduction to the use and understanding of optimization and modeling for upper-level undergraduate students in engineering and mathematics. The formulation of optimization problems is founded through concepts and techniques from operations research: Combinatorial Optimization, Linear Programming, and Integer and Nonlinear Programming (COLIN). Computer Science (CS) is also relevant and important given the applications of algorithms and Apps/algorithms (A) in solving optimization problems. Each chapter provides an overview of the main concepts of optimization according to COLINA, providing examples through App Inventor and AMPL software applications. All apps developed through the text are available for download. Additionally, the text includes links to the University of Wisconsin NEOS server, designed to handle more computing-intensive problems in complex optimization. Readers are encouraged to have some background in calculus, linear algebra, and relatedmathematics.