VISUAL INTERPRETATION OF CUSUM CHARTS
As mentioned above, a line which slopes downwards indicates that the results are below the average or the target value that
was selected. The steeper the line, the bigger the difference. A line that slopes upwards indicates that the selected values
are above average.
Changes in Slope
The human eye is a wonderful tool for seeing patterns and it is easy to imagine that every slight variation in a line is significant.
In this example, the extreme change in slope at the end of August is an important event but the others are debatable. For
example, at the end of July, the slope of the line is upwards, which indicates that the raw data values are above the overall
average, but not as much above average here as in September and October. This change may be significant or it could be a random
variation, it is difficult to tell from the data alone. If the date of change coincides with a known event, such as a change
of material or a process adjustment, then the data would support an assertion that something had affected the output of the
process. Below we describe some statistical significance tests that give an objective method for assessing a change in the
Gaps in the Data
Gaps in the data, such as the times during March and April when there was no production, put a horizontal step into the CUSUM
plot. It is usually possible to ignore such gaps by eye and make a visual estimate of the slope of the line to either side.
If there are many gaps and the plot becomes confusing, it is simple in Excel to change the horizontal axis so that it shows
batch number or successive measurements in sequence. A related problem occurs when a batch exists but there is no measurement
for it. In this situation, Excel interprets a blank cell as zero and the CUSUM score can be sent very high or low, creating
a vertical step. The solution is to either manually adjust the formulae so that they ignore the empty cell or to put in an
IF function to do it automatically.
Changes in Vertical Height
The actual vertical position of the CUSUM plot is not relevant and can be changed very easily by adjusting the value of the
first point in the sequence. In this example, the first point in the CUSUM is equal to the first measured value but it could
be set to zero, or the average, or some arbitrary value, which makes plotting convenient.
Individual extreme values put a step into the line but the slope remains the same to either side. If there are only a few
of these values, they can be ignored when looking at the charts. Alternately, the Excel formulae can be changed to exclude
Average Value or Target Value
For problem solving, it is simple and convenient to use the overall average as the fixed, offset value in the CUSUM calculations.
If a process target value is used instead, then the chart gives a clear indication if the process is running high or low.
If it continues to run high or low, then the line will eventually fall outside the scale on the chart and a reset will need
to be put in.
Find the Change Point
A graphical approach for finding the time when the average shifted is simple to use but does require a little judgment. Figure
6 shows the CUSUM for concentration of contaminant and two straight lines have been drawn through the points near the change
point. The judgment is in deciding how many of the data points to use for the straight lines. Sometimes, it is helpful to
mask the points nearest to the change time so that the lines are not distracted by a few points. Where the lines cross over
gives the time when the average changed and it is usually much clearer than an estimate from a simple trend chart. In this
example, the average went up starting on August 29.
Figure 6. An example of how a CUSUM plot can be used to estimate the change point.