Statistical Process Control (SPC) watches the variation in measured values statistically so that a drifting process is caught before it produces defects.
Collect process data
Variation over time
Limits and patterns
Review conditions and improve
Statistical Process Control (SPC) watches the variation in measured values statistically so that a drifting process is caught before it produces defects.
Every process varies. SPC separates that variation into common cause — the normal state of the process — and special cause, which is a signal to intervene.
In practice this is done with control charts. A point outside the control limits, or a run of points biased to one side or trending even while inside the limits, is treated as special cause.
The most common misunderstanding is the difference between control limits and specification limits. Specifications come from the customer; control limits come from what the process actually produces. They are different numbers, and drawing specification lines on a control chart defeats the purpose.
Specification limits come from drawings and customer requirements; control limits are calculated from process data. A part inside specification but outside the control limits means the process has changed — and left alone it will eventually breach specification too.
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What IYULAB provides in this area.
Questions that come up when evaluating SPC.
Calculating control limits needs a reasonable sample. Early on, collect data and watch the trend, then derive limits once the process settles.
No. Concentrating on the few characteristics that decide quality is more effective. Too many characteristics inflate measurement effort and bury the signal.
Manual measurement works, provided the interval and method stay consistent and something guards against entry error.
A look at your equipment and current workflow is usually enough to scope it.
Talk to an engineer