Most simulation tools available on the market today provide an interface to allow for model creation, a simulation engine, and a post-simulation analysis tool. The user interface is setup as either a pure coding environment, or a visual interface that creates code in the background, either way, coding is required to do any type of useful modeling. After the code is built and compiled, the simulation engine would run for a set amount of time after which the user is presented with the data to be either animated or charted.

In contrast, Dynamic simulation tools, like Simcad Pro, provide a complete new way of simulating and interacting with the models. The models are built using a graphical environment that does not generate code, nor does it require you to write code. In addition, it provides an optional coding environment in Visual Basic (similar to Microsoft Word, Excel ,...). After the  model is built, the simulation engine runs interactively (or in the background with updates), and dynamically displays the generated animation, charts, data to the user as it is collected and computed. Moreover, and since there is no coding interface to the engine, the user is able to modify the model dynamically during the simulation runs. As an example, a process can have its capacity or buffer space modified during the simulation in order to analyze the impact on the simulation. Another example could be changing the speed and capacity of the conveyors during the simulation runs.

Dynamic Simulation tools can play a major role in optimizing and improving any process based environment with ease and effectiveness that is unprecedented in this industry. The dynamic environment provides 4 main advantages over the static simulation tools
 

• Building the simulation model is done graphically, without the need to add code. All required parameters (queue wait, efficiency, utilization, resource wait, waiting for next, cycle time, lead time, ... ) are dynamically calculated for every model created. That results in a large reduction in the time required to build a model, hence reducing the model development cost and increasing the overall ROI of the project.
  
  
• The model can be tied in to existing systems (RFID, ERP/MRP, routings, ordering, schedules, ...) that constantly monitor and forecast the future of the operation in order to alert the operator to potential problems and bottlenecks that could occur in the future.
  
  
• The model can be used as a dynamic training tool for managers and operators where the model behavior changes dynamically during the simulation based on the interaction with the user. In other words, the simulation environment becomes a tool to recreate scenarios and allow the operators to interact with the model in order to achieve the best response possible.
   
• Optimization that is easily controlled and a "what-if" environment that provides the most flexibility possible.