While simulation tools have improved over time, most of these improvements have been in regards to simplifying technical hurdles, like importing data or making the user interface easier to understand. The complexity of how to break down a complicated, real-world process into concrete steps that can be modeled in a simulation language continues to be the most difficult part of using any package.
Worldwide, the average human is 5’6” (167cm) tall. This is a true fact – I know because I found it on the internet. However, is it a useful fact? Assume for a moment that you are a manufacturer of blue jeans. Would you take this average height value and then size all of your equipment so that it can only make jeans for individuals who are exactly this height? Now imagine your business was more narrowly focused in terms of your potential customer pool, e.g. men living in the United States. If you’re aiming for a smaller group, would it make any more sense to buy equipment that only makes one length of jeans? Or should you take the range of potential heights into account when designing your factory?
In this month’s case study, one of the chief goals of the simulation model was to test several potential operational modifications. When there are several changes to test, the questions arise:
Arena is innovating simulation of high speed systems. We’re solving bigger problems, faster, and more accurately to help our customers remain competitive in their fast paced business.
In Discrete Event Simulation one issue we must resolve is the number of concurrent entities in the model. If that number gets “large” then model run speed can be impacted. In the typical systems that we model this usually does not become an issue either because we will not have a large concurrent number or because our computers are really fast.