Shewhart Rules
Updated 2026-08-10
INTRODUCTION
English translation pending.
CORE DEFINITION
Shewhart Rules, developed by Walter Shewhart in the 1920s and extended into run rules, specify patterns on a control chart that indicate a process is no longer behaving randomly, such as a point beyond the three-sigma limits or seven consecutive points trending in one direction. Its core proposition is that a stable process still varies, so reacting to ordinary variation makes things worse, while ignoring non-random patterns lets real shifts persist. The key qualifier is correct limits: miscalibrated control limits produce either false alarms or missed signals.
SCAFFOLDING EFFECT
Reduce cognitive load
- Baseline establishment: compute the control limits from a period when the process was known to be stable. - Pattern reading: check for runs, trends, and points beyond the limits rather than just eyeballing. - Intervention discipline: act on the rule violations and leave the ordinary variation alone entirely.
Anchor fast decisions
Every process varies, and adjusting it in response to ordinary variation adds new disturbances on top of the original ones, which increases variance. Non-random patterns, by contrast, indicate a specific cause that can be found and removed. Separating the two is what makes intervention effective rather than meddlesome.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Western_Electric_rulesverified
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