Modern manufacturing processes have thoroughly incorporated
automation and repetitive processing. The use of
computer-controlled material handling systems to convey raw
materials through the multiple processing stages required to
produce a finished product is widely employed in industry
world-wide. Central to these systems are robot-served manufacturing
cells, or robotic cells. These cells perform a variety of functions
including arc welding, material handling, electroplating, textiles
creation, and machining. In addition, they are used in many
different industries, including injection molding of battery
components, glass manufacturing and processing, building products,
cosmetics, lawn tractors, fiber-optics, and semi-conductor
manufacturing. In the medical field, robotic cells are used to
produce components for magnetic resonance imaging systems, for
automated pharmacy compounding, to process nucleic acids, and to
generate compounds for tests in relevant biological screens. Cells
for grinding, polishing, and buffing handle many products,
including rotors, stainless steel elbows for the chemical and the
food industries, sink levers and faucets, propane tanks, flatware,
automotive products, and more. All of this has resulted with the
rapid growth of robotic cell scheduling. As manufacturers have
employed them in greater numbers and greater varieties, analysts
have developed new models and techniques to maximize these cells
productivity. Competitive pressures will result in the development
of more advanced cells and, hence, more sophisticated studies.
Therefore, robotic cell scheduling should continue to attract the
attention of a growing number of practitioners and researchers.
THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS is a comprehensive
introduction to the field of robotic scheduling. It discusses the
basic properties of robotic cells and outlines in detail the tools
most often used to analyze them. In doing so, the book will provide
a thorough algorithmic analysis of optimal policies for a variety
of implementations. The book provides a classification scheme for
robot cell scheduling problems that is based on cell
characteristics, and discusses the influence of these
characteristics on the methods of analysis employed. Implementation
issues are stressed. Specifically, these issues are explored in
terms of implementing solutions and open problems.
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