Controls

Controls

Angelia Wilkerson

Argosy University

MGT340 A01

Professor Edgar Arnold

October 18, 2014

Controls

The purpose of this report is to identify ways that statistical quality and control methods are used in regulating the weight of individual cereal boxes. After gathering the relevant data, it was important to determine the control limits; if any of the data points lie outside of these limits, we will know whether measures need to be taken to make corrections or if the current process is successful. This data was charted on a scatter plot, providing a visual tool in which to assess any data that is outside of the control parameters. The x-bar and R charts contain a center line, which represents the horizontal mean of the process, with the upper and lower control limits displayed by two more horizontal lines. When the weight of the boxes is in control, all data points will appear within the boundaries of the upper and lower control limits.

The data provided have been calculated to determine the control limits, which gave us an upper mean weight, in ounces, of 6.3696, a lower mean weight of 6.3087, plotted on an x-bar chart, as seen in Table 1. Table 2 shows the upper and lower control points plotted on the R chart to be between 0.196362 and 0.032365 ounces. The center line on the x-bar chart is 6.33915 ounces, with the center of the R chart being 0.11436 ounces. All of the data points within these limits would indicate that the process is in control. Unfortunately, the charts directed attention to points lying outside of the control limits. Both the x-bar and R charts clearly reveal that this process is out of control and that measures need to be taken to correct the weight in the cereal boxes. A slight positive linear regression pattern was observed between the fifth and ninth data points, suggesting that this where the calibration of the machine caused inaccuracies.

The calculations alone would not have provided the...