Analyzing Simulations

When you run the simulation for this model, two forecast charts are displayed.

The Total Cost Forecast (Figure 176, The Total Cost Forecast Chart, following) includes no assumption cells. It is displayed as a single value instead of a range of predicted values. The forecasted total cost is $26.73 for the pump (shown here with the Mean marker line displayed).

Figure 176. The Total Cost Forecast Chart

This figure displays the total cost forecast chart.

Because you entered a target and specification limits, the Flow Rate Forecast chart opens in Split View with the forecast chart first and then the process capability metrics, shown in Figure 177, The Flow Rate Forecast with Process Capability Metrics.

Figure 177. The Flow Rate Forecast with Process Capability Metrics

This figure displays the Flow Rate forecast with the process capability metrics.

Notice that marker lines are displayed for the LSL, Target, and USL values. (You might see different marker lines; the Mean and Standard Deviation marker lines have been removed to simplify the screenshot.) Because the LSL and USL are defined, the certainty grabbers are automatically set to those values. According to the value in the Certainty field for this simulation, 95.34% of forecasted values fall between 47.2617 and 53.9283, the specification limits. The mean is about one standard deviation lower than the target.

The distribution curve is normal. Looking at the process capability metrics, the Z-LSL shows the LSL is 1.63 sigmas below the mean. You were hoping to see a value of at least 3. The Cp capability index is lower than 1, so the short-term potential sigma level is less than 3.

You generate a sensitivity chart (Figure 178, Sensitivity Chart for the Flow Rate Forecast) to determine which of the flow rate variables has the most influence on the Flow Rate Forecast.

Figure 178. Sensitivity Chart for the Flow Rate Forecast

This figure displays the sensitivity chart for the Flow Rate forecast.

Figure 167, Sensitivity Chart for the Cycle Time Forecast shows that the flow rate variable with the greatest effect on the Flow Rate Forecast is the piston radius. Reducing the standard deviation of the piston radius should affect the overall flow rate variance and improve the process capability metrics. You wonder how reducing the piston standard deviation by 50% would affect the flow rate forecast quality. You decide to adjust the model and find out.