Discrete Event Simulation Explained

With discrete event simulation,Discrete Event Simulation Explained Articles the operation of the system is typically presented chronologically, based on a specific time frame. Each event that occurs in the system is reflected by a change in the results. There is a variety of methods for creating this type of simulation, where the results can be studied and used as the basis for strategic decisions.






There are a large number of industries and processes where discrete event simulation is successfully applied.  Some of these industries include manufacturing, business process re-engineering, heavy metals, mining, various processes in airports, logistics, healthcare, and more. Simulation can be used to: test how well assembly lines perform; determine the efficiency of line operators; and determine the result of an unexpected equipment failure or resource shortage.  For every action there is a reaction; simulation can help to determine the sequence of actions which is causing an undesired reaction.


Turning to an outside company can help your business identify problems in work flow, design, throughput and more.  In the past these problems were examined manually, and through static analysis.  Such methods resulted in many hours of work and left room for potential error. Companies like Visual8 Simulation Solutions have a wealth of experience in developing Discrete Event simulation models that can accurately represent your systems. Using state-of-the-art technology and employing experienced simulation model builders will help you to minimize your margin of error through the use of accurate time-based analyses.




There is a specific process involved in building a discrete event simulation model and ensuring a high-quality, validated end-product. First, data should be collected so that accurate inputs can be used to drive the software program.  Then a representation of the process is built using a discrete-event package in order to create the entire system flow (e.g. flow of information, product, personnel, etc.).  When the model has been validated against historical information then the simulation can be used to run a variety of scenarios.  Experiments are conducted to identify potential improvements, and to eventually determine the changes required in order to best improve the overall process / system.

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