Finding the Problem
Although the model used in the case study wouldn’t be recommended for starting your own business, it is valuable for the purposes of demonstrating several things. We will look at activity and resource utilization, cycle time, and overall resource usage.
Open the model called Case Study 1 – Analysis. Then double click the dashed resource connector between Gather Customer Information and the Tech 1 resource.
When you draw a resource connector, it defaults to a Get and Free connector. However, in this model, note that the connector between Tech 1 and the first activity is a Get connector. That means the resource is gotten at the first activity, but not released until later in the process. So he travels with the entity until a Free occurs after each oil change is complete.
Your 1st Assignment
The first thing we need to do is watch the simulation run to see what problems we can find before even looking at the output results. Then we will look at details of the output report in order to make a comparison of some simple changes we will be making to the model.
Simulate the model by clicking Simulation then select the Save and Simulate option.
The first thing you will notice is the second oil change activity is never used. Why is that when there are plenty of cars backing up waiting to be serviced? The reason is because of how the first resource (Tech 1) is being used. He takes the customer information for the first car, then goes with the car all the way through the process until the first oil change is complete. Then he is released and goes back to get the next customer’s information. By then, of course, there are no cars in the oil change bay. So when the 2 nd car comes in, it just goes to the first bay again because it’s empty. That means completely unutilized equipment and work space.
The second problem you will see is that the average cycle time (shown in the scoreboard) is 57.90 minutes for a 12 minute oil change. That means unhappy customers.
The third problem is that even though our last car arrived no later than 7pm, it doesn’t exit the model until close to 8pm. That means employees have to work overtime.
Now let’s look at the Smart Stats.
When asked if you want to see the results after the simulation, click Yes.
Note the Average Minutes Per Entry column. We see that customers waited (in the first input queue) to have their information taken for an average of 42.65 minutes.
Click on the Resources tab.
Our resource utilization is 45.52% for Tech 1, and 38.33% for Tech 2. So even though we have people waiting for an oil change, the resources are actually working less than half the day.
Click the Activities tab. See that most of the entities are waiting at the Gather_Customer_Information_inQ activity.
Your 2nd Assignment
That was a pretty dismal performance. Let’s see if we can make a simple change to the model to get some better results.
Close the Smart Stats and double click on the first resource connector again. Change the type to Get and Free. Then also change the two connectors going from Tech 1 to each of the Oil Change activities to Get and Free and simulate the model again.
As the simulation runs, note that both change bays are now being used, and the last car exits the process before 7:20pm.
View the output report and compare the results to the first simulation.
The average wait time in the first input queue has dropped from 42.65 minutes to just over 8.29. Plus the utilization has dropped on Tech 1.
Again, display the Activities tab. The non-value added wait time in the first activity has dropped from 90% of the overall cycle time to less than 30%.
Wait time typically increases processing costs, increases production inventories, and lowers customer satisfaction. So reducing that non-value added time is typically a significant concern in process improvement projects. Low resource utilization in and of itself isn’t necessarily a good thing. But what this result is telling us is that the process is much more efficient than the first one was.
Self Teaching Guide
- Your First Model
- Replications and Distributions
- Entity Arrivals
- Attributes, Variables and Action Logic
- A More Complex Call Center
- Model Building Techniques
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