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.
