question

There are many advantages of using a parameter table. Here are a few:

1. Parameters communicate model inputs to the user. If the user is a human user, they can easily find the parameters of any model, with a description of what each parameter controls. If a user wonders what the inputs of a model are, they can always check for a Parameter Table.
2. Parameters communicate model inputs to FlexSim. Tools like the Experimenter or the Reinforcement Learning tool can also be considered "users", because they, like a human user, attempt to adjust inputs to produce desired outputs. Instead of identifying the list of possible inputs for users in each tool separately, you can specify them in a single place, and all those tools can reference that single place. As we develop additional tools (for example, the Range-Based Job), they will also use parameters.
3. Parameters have type enforcement rules. This prevents the model from running with invalid inputs. For example, a parameter might control the number of people on a team. It is nonsensical to use text for that value, or a negative value, or a decimal value. Often, there is also an upper bound; in most cases, it would be nonsensical to set a team size to 1 million. Enforcement rules also make it easy for tools like the Optimization Job, Range-Based Job, and Reinforcement Learning tool to understand the total design space. You often select the Type based on the kinds of values that it allows. If a parameter controls the x-location of a Fixed Resource, you might consider using a Continuous parameter, with a meaningful upper or lower bound. If your parameter controls which picking strategy to use, you would likely use an Option parameter. The type you use depends on what the parameter controls in your model.
4. Parameters have an optional OnSet trigger. If you want, this allows you to define the code for the parameter, and attach it directly to the parameter. This code will fire whenever the model is reset, and whenever the value changes, even if it changes while the model is running. The OnSet trigger also fires before the Model Reset trigger, so it allows you to change the configuration of your model.

Pass-through parameters are somewhat different from the other types of parameters. They assume that the input value is owned by an arbitrary node in the model, not by the parameter. In this way, you can expose that node to the user, as an input. If a particular Global Table cell is an input value, then using a Pass-Through parameter allows you to show an arbitrary node's value to the user (including tools like the Experimenter and RL tool).

We have an issue on the dev list to improve the tutorials generally, and to make Parameters a part of the tutorials somehow.