Statistical Process Control (SPC) Basics

Quick answer: SPC uses simple statistics — mainly the control chart — to tell whether a process is behaving normally or something has changed. Points that vary randomly within the control limits are common-cause (normal) variation; points outside the limits or showing non-random patterns signal a special cause to investigate.

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A control chart separates normal variation (within limits) from special causes (outside).

Common Cause vs. Special Cause

  • Common-cause variation is the natural, random noise inherent in a stable process. You improve it by changing the process itself.
  • Special-cause variation is an external, identifiable disturbance — a tool wearing out, a new material lot, a setup error. You find and remove it.

The whole point of a control chart is to tell these two apart so you don't "fix" random noise (which makes things worse) or ignore a real signal.

How a Control Chart Works

You plot a process measurement over time against a center line (the average) and upper and lower control limits (typically ±3 standard deviations). As long as points fall randomly within the limits, the process is "in control." A point outside the limits, or a run/trend, flags a special cause to investigate.

Process Capability: Cp and Cpk

Being in control isn't the same as meeting customer specs. Capability indices compare the process spread to the spec limits:

  • Cp measures whether the process is narrow enough to fit within the spec, ignoring centering.
  • Cpk accounts for centering too — a low Cpk means the process is drifting toward (or past) a spec limit.

A common target is Cpk ≥ 1.33. A process can be perfectly in control yet still incapable if it isn't centered or is too wide.

Frequently Asked Questions

Are control limits the same as spec limits?

No. Control limits come from the process's own variation; spec limits come from the customer. A process can be in control but out of spec, or vice versa.

Do I need software for SPC?

It helps at scale, but the concepts work with a simple chart. The discipline of plotting and reacting correctly matters more than the tool.

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