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This would help in balancing the utilizations of the resources and reduce the waiting time in the longer queues.
As far as the changes in the system flow is concerned, there is one change that can increase the efficiency of the system. Instead of having another resource for food items, Starbucks can have two Cash Counter and both of these resources can serve food items to the customers there itself.
The model was renovated with the above suggestions and here is a glimpse of the new model — Changes — 1.
The process module and hence the queue for Food items was removed 2. The Resource capacity for Cash counter was increased from 1 to 2 3.
The service time for Cash counter was increased to accommodate the service of food items Now, the model has only 3 resources and the resource capacity of Cash counter is now 2.
Comparing the results — We discussed the Arena results for the original model earlier and by interpreting the results we came up with a few suggestions and implemented those to obtain an improved version of the model.
Now, we will statistically compare the results of the changes that were incorporated in the model. Rockwell Software also provides a complimentary tool with Arena called Process Analyzer.
Using Process Analyzer, we can compare the results of different models or different scenarios of the same model statistically and plot the graphs accordingly.
The Process Analyzer was used to compare 3 scenarios — 1. Original Model with capacity 1 for each resource. Food Item resource present. Cash 2 Model with capacity 2 for Cash counter resource.
Food Item resource absent. Here is a snapshot of the Process Analyzer scenarios — It can be seen that the average customer time is reduced significantly 2.
The time is even further reduced for Scenario 3 1. After comparing the responses of Average Customer Time for all the above scenarios, graphs were plotted for the response variation across these scenarios.
Here, we get a visual perception about the response and the best scenario is marked in red. Both the charts depict that the improved model with capacity 2 for both the resources is the best scenario.
In this section, we compare the results of PAN statistically to prove that Scenario 3. Below is a table showing the output data from PAN which gives information about the maximum, minimum, average value of the response.
Scenario no. Original Model 0. Cash 2 9. Cash and Hot 2 0. So, this case proves to be the best case.
It can be concluded that for scenario 3, an assertion that the average customer time in the system will lie between 1. A deep analysis was done on the output results of Arena and it was observed that the average customer time in the system during rush hours was large enough for Starbucks to lose potential customers and downgrade the business.
By probing into the flow of counters of the system, it was observed that the waiting time in the queue at the cash counter was significantly large as compared to other queues.
So, taking into consideration the resources available at Starbucks, a suggestion was made where the food items would be served at the cash counter itself and another cash counter would be added.
To increase the efficiency economically, it was suggested that the server for Cold Beverages should be cross-trained to serve Hot Beverages as well.
The new model was compared statistically for the Average Customer time in the System using a software called Process Analyzer and it was found that the new, suggested model has a statistically significant decrease in the Average Customer time as compared to the original model.
Hence, with certain suggested changes in the management and operations at Starbucks, there can be an increase in their Business.
Again, there can be ample suggestions on and modifications in the model to optimize the output both economically and commercially; but we have discussed only one of them.
Sadowski, Nancy B. Zupick, Rockwell Automation 2. You just clipped your first slide! Clipping is a handy way to collect important slides you want to go back to later.
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