ISO 9001
section 7.5.2 talks about controlling processes. Some processes are controlled because the
quality of the resulting product cannot be determined once the process is
complete as 7.5.2 indicates, but there are many other good reasons to perform
process control. Collecting data on a
process for the sake of collecting data is of little value. It is best to collect and analyze process
data.
There are many tools for controlling processes. The one I’ll talk about today is statistical
process control using Shewhart Control Charts.
Walter Shewhart developed control charts around the turn of the last
century. They are tried and true, and I
have used them to control a number of processes.
Control charts are based on the theory that the mean of a sample
from a normal distribution is normally distributed, with the mean equal to the
distribution mean and a standard deviation equal to the distribution standard
deviation divided by the square root of the sample size. In fact, for distributions that are
non-normally distributed, the mean tends to be normally distributed. So the technique is robust.
Shewhart control charts control the process mean by
controlling the sample mean. They
control the process standard deviation by controlling the sample range. Control
is applied by calculating control limits for the sample mean and sample range
and plotting the sample mean and range on mean (XBAR) and range (R) charts
respectively.
When a mean or range exceeds its control limit, we say that
the process has gone out of control. A
data point that exceeds a control limit causes us to stop the process to
understand the root cause of the out of control condition, or, more likely we
make a process adjustment and note the adjustment on the chart. For example, it is common for a machine tool
to go out of control due to tool wear. A
simple machine adjustment brings the machine tool back into control.
One complaint about Shewhart Control Charts is that they are
complicated to set up. Some also
complain that they require the machine operator to stop and make
calculations. In the old days,
calculators and computers were not available, and it was more work for the
machine operator to calculate the mean and range. In the digital age though, these complaints
are unfounded. Software to create
control charts is easy and inexpensive to come by, and some inspection tools
actually do the work of calculating and plotting the control charts.
I put together a simple Excel spreadsheet that will do all
the work for you. You can download it here. The spreadsheet has some fictitious data placed
there so you can see the charts in action.
You can easily overwrite it with actual data. Instructions for creating a control chart
using the spreadsheet can be found here. Instructions for using the control chart spreadsheet
are also provided, and you can download them here.
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