Information & Training | SPC and Statistical Methods for Process Improvement.

Statistical Process Control Charts.

Variation is inherent in every process; it is virtually impossible to get to the point where every aspect of the operation of a process is identical to every previous operational experience. If you go into sufficient level of detail variation will become evident. Variation in itself is not a problem, variation only becomes a problem when it causes process outputs to arise which result in product or service performances which do not meet customer expectations.

– Statistical Process Control Charts identify “special causes” of variation, which is anything which leads to an observation beyond a control limit, i.e. outside the UCL or the LCL.

– They are running records of the operation of a process.

– With the control chart you can identify any exceptional cause of variation, i.e. a once off change, you can identify drifts in the process, you can identify patterns, cycles, etc..


Interpreting Statistical Process Control Charts (X and R-Bar):

A point above the Upper Control Limit or below the Lower Control Limit may mean that a special cause of variation may be present.

Consider has there been an error in control limit calculations or plotting.

Has there been a change to the method of measurement, has a standard changed?

Has the process change at that point been a once-off or is this part of a changing trend?

Further measurements will help answer some of these questions.


Example – Tests for Special Causes – Trends.

Statistical Process Control Charts

SPC & Statistical Methods for Process Improvement.
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Trends can arise due to deterioration within an item of process equipment, for example drill bits can wear over time. Maintenance schedules need to ensure that “wear and tear” is not allowed to drive out of control situations. In manual operations, staff can become tired, for example, an inspection process that requires staff to examine samples under microscopes is specifically prone to a “tiredness” effect, where potential reject samples are deemed good and visa-versa. Suitable work breaks, job rotations need to be in place. Trends can often be seen over the course of a day. In the morning the operating environment may be cool then as the day progresses, the ambient temperature increases. This can affect the operation of test and measurement equipment. The solution will be to ensure stable operating environments.


Example – Recurring Cycles.

Where a recurring cycling of results is seen, it may indicate some form of fluctuation into the inputs of a process, for example fluctuations in input voltage or current. There may be systematic changes happening within the operating environment, such cycles could relate to rotation on staff, or where tasks are being split between a number of individuals, i.e. 3 staff performing a task, so each person takes every 3rd task. Wear and tear of equipment can also result in output cycles. In a pick and place machine, there may be two “pickers”, one of which is performing differently to the other.

Statistical Process Control Full Details

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SPC & Statistical Methods for Process Improvement.

  • Process Capability. Variability Reduction. Statistical Process Control.
  • Pre-Control. R&R Studies. 
  • Process capability indices Cp, Cpk, Cpm, Capability ratio.
  • Performance indices Pp and Ppk.
  • Variable Control Charts.
  • Attribute Charts.
  • Pareto Charts.
  • Individual – X Charts.
  • Histograms / Process Capability Analysis.
  • Scatter Diagrams.
  • Etc. … Etc. …
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