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Operating model

Pareto chart

Where do the problems concentrate, and did that shift after the rev rule?

Which count
Twelve weeks. wrong revision leads with 86. Bars are counts. The line is cumulative percent. The dashed line is 80 percent. 86wrong revision3771seat scratch6824missing seal7922wrong confirm day8819count mismatch978mixed heatcount0%800
Last 10 production days. scratch leads with 17. Bars are counts. The line is cumulative percent. The dashed line is 80 percent. 17scratch536wrong confirm day724wrong revision843missing seal942count mismatch0mixed heatcount0%800
Two windows from one control. The full window is led by wrong revision. The recent window is led by scratches.
How this sheet sits with the others

Across twelve weeks, wrong revision leads with 86, then seat-face scratch with 71. Missing seal is 24, confirm posted on the wrong day is 22, count mismatch is 19, and mixed heat is 8. In the last 10 production days after the rev rule, scratches lead with 17 and wrong revision is 4. Mixed heat is 0 in that recent window. The chart shows where the counts concentrate. It does not show the sequence of days, and it does not test a cause.

What it makes visible
The twelve-week counts and the last 10 production days after the rev rule.
When it is useful
When the team needs to see whether the leading problem changed after a countermeasure.
Who uses it
Mara Ellison and Priya Shah, comparing the long window with the days after 21 September.
What it takes
Counts by category for the full window and for the recent window.
What it leaves
The full window is led by wrong revision, at 86. The recent window is led by scratches, at 17, with wrong revision at 4.
The underlying record
Wrong revision, seat-face scratch, missing seal, a confirm on the wrong day, count mismatch, and mixed heat are the counts the check sheet samples and the A3 is opened against.

Where these facts go next

What this sheet still leaves out

It has no time series and no cause test.