Statistical Process Control (SPC) uses control charts to detect when a process is drifting out of control before it produces defective parts. By plotting measurements over time and comparing them to statistically derived control limits, SPC distinguishes between normal process variation and assignable causes that require intervention.
The most common SPC tools are X-bar and R charts for variable data, and p-charts and c-charts for attribute data. When a measurement falls outside control limits or shows a non-random pattern (trends, runs, cycles), the process is signaled as out of control and operators investigate the cause.
SPC is required by many quality standards (IATF 16949 for automotive, AS9100 for aerospace) and is a prerequisite for process capability studies. Manufacturing software that automatically collects measurement data and generates control charts makes SPC practical for high-volume operations where manual charting is not feasible.