The online course in Statistical Process Control is intended for
quality practitioners, engineers and managers who
are responsible for introducing and using SPC. Statistical Process
Control is used by many industries to monitor the performance of their
Statistical Process Control is easy to use. It is
based on simple charts that can be kept up to date, and interpreted
with a minimum of training. It is also easy to computerize, and many
excellent software packages are available.
Despite its simplicity, SPC is based on sound and subtle statistical
concepts. These are often misunderstood leading to SPC being used incorrectly
and give misleading results. Managers and engineers responsible for
the operation and implementation of SPC should be sure they understand
Statistical Process Control is about identifying process changes
quickly, but not overreacting to normal part-to-part Variation.
The first section of our SPC course explores 'process variation', ways
of measuring it, and the distinction between 'common' and 'special
causes'. It also emphasizes the importance of Normal Distribution.
After becoming familiar with variation, we move on to 'Process
Capability' and 'process performance'. These are important
requirements of supplier accreditation systems and powerful tools in
predicting process yield. They also help to identify opportunities
for process improvement.
The next section covers Control Charts for Variables.
I've approached control charts by building up from run charts. This
allows me to emphasize the importance of subgroups in separating process
accuracy and process precision. We then go on to look at how to apply
control charts in practice, and how to interpret the results from control
The fourth, and final, section covers Control Charts for
Attributes. By now you are familiar with control charts and
will have little difficulty grasping the principles and operation of
this type of control chart.
After completing the course you will be able to apply Statistical
Process Control effectively in your workplace. You will also
be able to interpret the results from SPC systems properly, avoiding
common misconceptions and using them to identify opportunities for