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2.1.5 Using a location element to simulate resource deployment

In this part of the tutorial demo we are going to use a location element to capture the effect of geographical distribution of customers (and therefore resources). The customers are spread across ten sites, so the resource equipment required to provide the service also needs to be spread across ten sites. Spare resource capacity at any site cannot be used to satisfy demand at another site, which increases the amount of slack unused capacity.

  1. In the Editor, right-click on the Location 1 element that you created earlier and select Details from the icon menu. The Details dialog opens.
  2. Enter Sites in the Unit field and 10 in the Sites field.

Figure 1: The Details dialog for Location 1

As this is a simple example, the Sites input is a constant (10), meaning that the resources will be distributed across ten sites from Y0 onwards, and the number of sites will not increase.

  1. Use the Connect tool to make a connection from Location 1 to Resource 1. A blue line will be drawn connecting the two elements.

Figure 2: Linking Location 1 to Resource 1

Note: the resource must be physically present in all ten locations; hence the location element is linked to the resource rather than to the service.

  1. Run the model by pressing <F5> or by selecting File/Save and Run.

You will see that the graphs in the results program will have updated automatically to reflect the influence of the new inputs. What do you notice?

  1. Look at the Utilisation Ratio graph. Can you explain how it has changed? Look at the Capacities table to help you explain these results.

The Used Capacity of the resource is unchanged, but the Installed Capacity is much higher (500 in Y1 c.f. 50 in Y1 previously) because the location element specifies that you have to have at least one unit of the resource installed at each of the ten sites, each unit of which has a capacity for 50 customers. This is called One for One distribution and is the simplest type of distribution. The increased Installed Capacity and corresponding Slack Capacity result in the observed initial low Utilisation Ratio for the resource.

Figure 3: Updated Utilisation Ratio graph and Capacities table

If you look at the Capacities results more closely you will notice that the Installed Capacity is 500 from Y1 onwards and then stays constant in Y2 and Y3, as the number of customers does not exceed 500. However, once the number of customers increases to 605 in Y4, the Installed Capacity increases to 650 (i.e., three extra units of the resource). However, the one-for-one distribution is making the assumption that, after Y3, all additional customers are at one site only, so is only adding enough resource units to meet the extra demand based on this assumption. In reality, if the extra customers are distributed across all ten sites, then ten additional resource units would be required, rather than just three (two resource units per site), depending on when, at each individual site, the number of customers exceeded 50.

Things that you should have seen and understood

One for One distribution


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