Measure
Data Collection Plan
Carry CTQC definitions into practical collection methods, sampling plans and ownership.
Control · Interactive CI tool
A control chart plots observations in time order against limits estimated from a chosen baseline. It helps distinguish routine variation from patterns that warrant investigation.
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Use it when repeated observations have comparable definitions and a defensible sequence or subgroup structure.
It supports more disciplined responses than treating every rise or fall as a process change.
Use Pareto for category priorities and Process Capability to compare a sufficiently supported process model with specifications. Control limits are not customer acceptance limits.
Fictional example snapshot
A fictional supplier has 20 baseline samples of 100 inspected units each, with defective-unit counts 8, 10, 12, 10 repeated five times. The pooled baseline proportion is 200/2,000 = 10%.
| Sample of 80 | 18 defective units = 22.5%; upper proportion-chart limit is approximately 20.06% |
|---|---|
| Sample of 120 | 12 defective units = 10%; upper limit is approximately 18.22% |
| Completed conclusion | The first sample exceeds its upper limit; the second does not. Investigate the first sample without claiming a specific cause. |
These figures illustrate the method; they are not clinical instructions, universal targets or verified results from a real organization.
Read the complete worked example and its interpretationThe full guide includes prerequisites, interface-specific steps, two fictional examples, common mistakes and interpretation help. It is available without registration.
Control Chart Builder: guide & examplesOpen Control Chart BuilderMeasure
Carry CTQC definitions into practical collection methods, sampling plans and ownership.
Analyze
Compare observed variation with explicit specifications and documented distribution assumptions.
Analyze
Investigate causes with evidence, cause trees, validation and linked 5 Whys.