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SIGMA—A graphical approach to teaching simulation

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Abstract

SIGMA (Simulation Graphical Modeling and Analysis) is a graphics environment for building, testing, and experimenting with discrete event simulation models on personal computers. SIGMA is based on “event graphs,” a concept that utilizes symbolic representations to concisely depict large, complex discrete event systems (like airports, hospitals, and factories) so that they can be understood more easily. SIGMA, the computer animation of event graphs, captures the logic of the computational processes underpinning a simulation.

SIGMA was developed to improve the quality of simulation education. Problems addressed during a semester were: how to convey simulation concepts more easily, how to help students understand the many complexities associated with this topic, and how to help students build realistic computer models of large, complicated systems. In SIGMA, stochastic systems are represented as simple, dynamic graphs. Simulation models are easily created by drawing these graphs on a computer with a mouse. Students quickly learn how various events in a system interact by observing SIGMA’s graphics displays. SIGMA has proved itself to be a valuable educational tool, not only for courses that teach simulation, but also for courses that use simulations. Furthermore, SIGMA’s capability to model very large systems has led to successful industrial applications.

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ABOUT THE AUTHOR

Lee Schruben is on the faculty of the School of Operations Research and Industrial Engineering at Cornell University. He received a B.S. degree from Cornell in 1968, a M.S. degree from the University of North Carolina in 1973, and a Ph.D. from Yale University in 1975. His research interests are focused on manufacturing systems design and analysis, specializing in simulation methodology. Professor Schruben is the author of numerous papers, three of which have won national awards. He is also the creator of the SIGMA software environment.

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Schruben, L.W. SIGMA—A graphical approach to teaching simulation. J. Comput. High. Educ. 4, 27–37 (1992). https://doi.org/10.1007/BF02940978

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