# Resource Management in FlexSim Modelling: Addressing Drawbacks and Improving Accuracy
## 3 Process Flow Model, 3D Model and Experimental Results
### Insight of 3D Model: Stage 2  
Finally, we will explain why exact waiting times of happy customers are obtained in Stage 2. Recall that, in Stage 2, additional resources were introduced in the form of events in which customers entering and leaving the service desk act as a mechanism to trigger updates to the wait times. The event of a customer entering the service area is the same as the event of a customer leaving the waiting line, since a customer leaving the waiting line must enter the service area to receive service [25].  
Although some customers will be pulled into the unhappy exit because the waiting time exceeds 200 s, this mechanism is activated by the unhappy sink, not by the mechanism of customers leaving the waiting line. The results of our simulations confirm this. When an option was added to the _Back Order Reevaluation Event_ to reflect a customer entering the service desk, the statistics for the waiting times of happy customers were the same as those for Stage 1 of the 3D model. Hence, the resource that changes the waiting times of happy customers is the event of leaving the service desk.  
As mentioned earlier, in the 3D default model, the waiting time of a happy customer may exceed 200 s. This happens when the customer's waiting time exceeds 200 s but a new customer has not yet entered the waiting line, as the customer's waiting time, according to the system records, is still less than 200 s. At this time, if the service area is free, the  
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline  & **Min.** & **Max.** & **Average** & **S.D.** & **Count** \\ \hline Process Flow Model & 0 & 199.99 & 127.36 & 53.60 & 454 \\ \hline
3D Model: default & 0 & 354.84 & 162.38 & 70.88 & 456 \\ \hline
3D Model: Stage 1 & 0 & 294.16 & 158.32 & 70.85 & 451 \\ \hline
3D Model: Stage 2 & 0 & 199.83 & 127.13 & 58.29 & 447 \\ \hline
3D Model: Stage 3 & 0 & 199.83 & 127.13 & 58.29 & 447 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Statistics of waiting time (in seconds) for happy customers.  
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline  & **Min.** & **Max.** & **Average** & **S.D.** & **Count** \\ \hline Process Flow Model & 200.00 & 200.00 & 200.00 & 0 & 302 \\ \hline
3D Model: default & 200.10 & 398.83 & 237.88 & 35.40 & 278 \\ \hline
3D Model: Stage 1 & 200.10 & 288.15 & 222.53 & 18.52 & 274 \\ \hline
3D Model: Stage 2 & 200.10 & 292.19 & 223.74 & 18.62 & 293 \\ \hline
3D Model: Stage 3 & 200.10 & 229.77 & 210.35 & 7.96 & 293 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistics of waiting time (in seconds) for unhappy customers.  
customer will enter the service area to receive services, meaning that the waiting time of this happy customer will exceed 200 s. This problem of inaccurate measurement can be avoided by making sure that the customer's wait time is updated when the service area becomes available. This is the aim of Stage 2 of the 3D model. When a customer leaves the service area, the waiting times of the customers in the queue are updated, and the system can determine whether the customer at the front of the waiting line can enter the service area. A customer whose wait time exceeds 200 s is pulled into leaving unhappily, and cannot enter the service area. If the wait time is less than 200 s, however, the customer can enter the service area. In this way, the waiting times of happy customers can be accurately recorded.  
Sometimes, when a customer enters the queue, other customers have been waiting for more than 200 s, and the service area is still busy and cannot provide services to these customers. At this time, these customers will be pulled into the unhappy customers' exit. This creates waiting times of more than 200 s for unhappy customers. To address this problem, a timer must be used. In Stage 3 of the 3D model, if the system has not updated the waiting time within 30 s, it will be automatically updated; however, this approach can only reduce the measurement error to within 30 s.