Discrete Event Simulation

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Discrete Event Simulation (DES) models how a system, with events in a discrete time limited sequence, operates. DES has been most notably been used in the disciplines of industrial engineering, control systems engineering, and operations management. DES models of systems with stereotyped functions and high repeatability are the most accurate however the concept can be generalized to most map-able systems or processes. At its core a discrete event simulation model consists of and entry node, with raw work items coming in at a specified rate, at least one intermediate processing node in which raw work items are transformed into completed work items at a specified rate, and an exit node to signal that completed work items have exited the system. Queues can occur between any given node in a DES model.

In mapping the current state of a system in healthcare, DES provides a way to identify bottle-necks, over or under-utilized resources, and guide patient scheduling decisions. The primary purpose of DES occurs after the initial mapping of a system has occurred. A DES model allows the user to alter any of the variables of an existing model digitally prior to real world implementation in order to see how workflow will be impacted.

Example

McDonald's serves as a common example of discrete event simulation in industry. The company maintains a model that includes all of the timing and movements involved making each product on the menu. If they want to change an existing menu item or add a new item to the menu they can alter their simulation accordingly, prior to real world implementation, to define the most efficient workflow.

A paper by Dr. Booker and Dr. O'Connell outlines how DES can be used in the management of time sensitive, high demand, and expensive resources in radiology ([1])

Simulation Tools

A number of DES tools exist with varying utility. Simul8 is a visually driven process simulation modeling system. ([2]) Simulink is a process simulation modeling system that integrates with the MATLAB environment. ([3]).


Submitted by Ryan O'Connell