In any production environment, discrete event simulation is a powerful tool for the analysis, planning, and operating of a manufacturing facility. Operations managers can use simulation to improve their production systems by eliminating bottlenecks, reducing cycle time and cost, and increasing capacity utilization. Offering a hands-on tutorial on how to model traditional applications to optimize production operations, Simulation of Industrial Systems: Discrete Event Simulation Using Excel/VBA―
· Introduces the Design Environment for Event Driven Simulation (DEEDS), an original simulator, which facilitates the modeling of complex situations using four (self-contained) nodes: source, queue, facility, and delay.
· Demonstrates how to use discrete event simulation as a powerful tool for the analysis, planning, design, and operation of diverse production systems
· Shows how to model application areas such as facilities layout, material handling, inventory control, scheduling, maintenance, quality control, and supply chain logistics
· Integrates the design of experiments and optimization techniques for improving production systems
With the comprehensive instruction provided within these pages, in combination with the flexibility of the DEEDS program environment, operations managers will be able to harness the power of discrete event simulation to streamline their production environments.
The authors have created a website with a variety of teaching aids that professors will be able to access
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Serving a dual purpose, this book is written for novices who want to learn the basics of discrete simulation and professionals who wish to use discrete event simulation to model systems. The authors assume that the reader has a fundamental familiarity with modeling concepts and Excel, however, they do not assume prior programming experience. Organized into three parts, this book presents the concepts of discrete simulation, covers the design Environment for Event Driven Simulation (DEEDS), and discusses a variety of applications using DEEDS. In this work, the DEEDS research features are demonstrated and genetic algorithm techniques are integrated into the DEEDS environment to produce a powerful tool.
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