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How Rule Combinations Increase False Positives

Interactive micro-lesson showing how Monte Carlo simulation estimates false positive risk when you enable more SPC rules.

8 min readIntermediate

What happens when a stable process gets watched by more and more rules?

You usually catch more real signals, but you also create more false alarms. This lesson lets you test that tradeoff with a server-side Monte Carlo simulation.

What a false positive means

A false positive happens when the process is actually in control, but the chart still signals that something may be wrong. In real operations, that can lead to unnecessary investigations, extra adjustments, and wasted time.

The more rules you enable, the more ways a sequence can trigger. That usually makes the chart more sensitive, but it also raises the chance that an in-control sequence will look suspicious.

Build your simulation scenario

Select the rule combination you want to test, choose how many points each simulated sequence should contain, and then run the Monte Carlo model.

Simulation results

The simulation generates many in-control sequences and counts how often the selected rules still fire at least one alert.

Run the simulation to estimate the false positive risk for your selected rule set.

When to use fewer or more rules

Use fewer rules when

The cost of chasing false alarms is high, the process is already stable, or the team tends to tamper with the process after every signal.

Use more rules when

You need earlier detection, the process is high risk, and the team can investigate signals calmly without over-adjusting the process.

Try It Yourself

Want to check YOUR process capability? Paste your data into our free tool.

Open SPC Quick Check

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