What is a control chart?

A control chart separates normal process variation from signals that something has actually changed. It tells you when to act and when to leave the process alone.

How to use this tool

Paste two columns from Excel or CSV: a date or label in column one, a numeric value in column two. You need at least 30 data points. Spec limits are optional.

Control vs. spec limits

Control limits show what the process does. Spec limits show what the customer requires. A stable process can still fail spec if it is not capable.

Paste your data

Paste directly from Excel (tab-separated) or CSV. Minimum 30 data points required.

Leave blank to auto-calculate (±1σ)
Process summary
Control chart
Data
Measured valuesYour actual data points in time order.
Average
Center lineThe mean of all observations.
UCL / LCL
Control limits (±3σ)Points outside these signal a special cause: something real changed in the process.
USL / LSL
Spec limitsCustomer or design requirements. A stable process can still fail spec if it is not capable.
Special cause
Special cause variationA point beyond the UCL or LCL. Investigate and remove the root cause.
Outside spec
Outside spec (within control)Stable but not capable. The system needs redesign.
Common cause
Common cause variationNormal noise. Reacting to these individual points makes the process worse.
Click a point to inspect  ·  Scroll to zoom  ·  Drag to pan
Paste data above and click Build chart to get started
Distribution statistics
Distribution / bell curve
Normal curve
Normal distributionTheoretical bell curve from your data mean and standard deviation.
UCL / LCL
Control limitsPoints beyond these are special cause.
USL / LSL
Spec limitsArea outside these lines represents defects.
Sigma lines
Sigma zones±1σ ~68%, ±2σ ~95%, ±3σ ~99.7%
Build the control chart first to generate the distribution

Ready to act on what you found?

Special cause variation and process capability issues are improvement opportunities. Let's talk through what your data is telling you.

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