Control charts monitor variation to catch drift early.
Control charts (X̄-R, p, c) track process mean and variation against control limits ±3σ to distinguish common-cause from special-cause variation; rules (Western Electric) detect trends and shifts. Prevents defects by acting early.
A shaft-diameter chart shows 7 consecutive points above the centre line, signalling a shift.
Statistical process control shows whether a process is stable, so you can act on real drift rather than normal variation.
Control charts monitor variation to catch drift early.
Statistical process control shows whether a process is stable, so you can act on real drift rather than normal variation.
A plot of a process statistic over time with control limits set from the process variation, showing whether the process is in control.
Common cause variation is the normal random spread of a stable process, while special cause variation comes from an identifiable event that should be investigated.
Typical applications include plotting the diameter of parts on an X-bar chart during production, setting control limits on a filling process and stopping a machine when a point falls outside the control limits.
Study "Quality control" first (topic 33 of 102 in Manufacturing, Robotics & Systems). It covers the groundwork this topic builds on.
Rational subgrouping. Out-of-control signals. Phase I and II.
A shaft-diameter chart shows 7 consecutive points above the centre line, signalling a shift.
The next topic is "Six Sigma and lean", which builds directly on this one.
It is classed as Beginner in Manufacturing, Robotics & Systems (topic 34 of 102). It is an entry-level topic. It relies only on basic school mathematics and the ideas introduced earlier in this discipline.
Want to practise? Open the interactive course for quick checks, quizzes, simulations and progress tracking.