1. SPC (Statistical Process Control)
What it is
SPC is a statistical technique which compares current process output against a historical template.
The template is usually based around a centre value with ± 3 standard measures of variation (of the characteristic being measured).
The objective is to keep the current process stable, within these ± 3 control limits and to limit variation within them.
Industry-standard rules are adopted: If data from the current process approaches these control limits or forms non-random patterns within the limits, then appropriate action to control the process is taken.
No reference to specifications are made in SPC
SPC was developed by Walter Shewhart and others, and many traditionalists refer to SPC charts as Shewhart charts
SPC (Statistical Process Control) v1.ppt

2. SPC (Statistical Process Control)
What it is
Special
causes
act
Common
causes act
UCL / LCL = Control Limits
UCL
LCL
Centre
Line
The UCL/LCL is set by default at ± 3 standard measures of variation (of the characteristic being measured).
Additional control limits can be added, but usually industry-standard rules apply.
How to use it
Detailed information regarding how to construct an SPC chart manually, how to run one in Minitab, how to select the correct SPC chart, and the main industry-standard rules are found in the aTQ training material referred to in the References.
SPC (Statistical Process Control) v1.ppt

3. SPC (Statistical Process Control)
Example
Chart rules
follow industry
standards or
adapt to suit
Actions to
follow if Rules
are breached
Standard Shewhart Control Factors, used to manually
calculate centre lines
and limits.
Table for data collection
SPC (Statistical Process Control) v1.ppt

4. SPC (Statistical Process Control)
How it helps
SPC charts must be seen alongside Process Capability graphs and indexes.
References
ASG aTQ training modules:
8.4, 8.5, 8.6, 8.7 : SPC (and non-SPC control)
ASG “seniors” aTQ training module 1.5 : Capability
SPC (Statistical Process Control) v1.ppt