For many systems, using animation to visualize system behavior greatly enhances your ability to spot problems.
Bottlenecks that might get lost in a mountain of statistical output are readily apparent as long queues in an animation.
Once our simulation program is running, we run experiments to explore our system.
Many computer programs produce simple numeric answers.
In the public sector, the motivations most often are to provide for the well being and safety of the public, and to reduce the risk of negative events, such as injury or death.
Most systems of interest are complex, and many are controlled by computer programs that allow them to react to current circumstances and intelligently modify their behavior in real time or near real time.
We can't include every last system detail in a model. So, through a process of abstraction, we select those details that are most critical to characterizing the operation of the system. We must validate the model to assure that it properly represents our system.
A simulation tool that provides 20 kinds of conveyor belts may be of little use to you if what you have is the 21 type yourself.You can't simply run the model once and say the answer is 10.5 minutes.If the model you've built is realistic, the answer may be 8 minutes on a really good day and 20 minutes on a horrible day.Simulations almost always result in the discovery of unforeseen bottlenecks and deficiencies.Given the complexity of the systems we model, it should come as no surprise that our initial designs are rarely perfect. In the early going, when your simulation produces incorrect results, you'll discover that you've incorrectly modeled a system component.