Automated scrap and quality-cost reporting for a quality team
A quality-engineering team turned years of scrap detail into a monthly report with trends and top causes, generated in minutes instead of most of a day.
The quality team tracked scrap in monthly spreadsheets. Producing the management report (trends, top causes, comparisons) was a manual job that ate most of a day, and the totals between sheets sometimes disagreed.
Leadership wanted several views at once: month over month, year over year, a 12-month average and the full-period picture, plus how the cause structure was shifting. That was too much to keep up by hand.
Months of inconsistent spreadsheets
Scrap detail lived in sheets that did not line up cleanly.
Many comparison views wanted
MoM, YoY, 12-month and full-period were heavy to build by hand.
Cause structure kept shifting
The top causes changed month to month and were hard to track.
Totals sometimes disagreed
Different summary sheets did not always reconcile.
We reconciled the full scrap history and generated a consistent monthly report: the latest month against month-over-month, year-over-year, the 12-month average and the full period, plus the top causes and how the cause structure is shifting over time.
The report separates real signal from noise (a one-off versus a trend) and never invents numbers: it reports only what the data supports, with a checking view so the totals are verifiable.
- Ingest and reconcile the full scrap history
- Monthly report: latest month vs MoM / YoY / 12-month / full period
- Top causes and cause-structure-over-time
- A checking view so the totals are verifiable
Built once, then every month in minutes
One expensive problem, proven before it scales. The A1 to POC method, run in weeks not quarters.
The report stopped being a chore and started being early warning.
- The monthly report goes from a day's work to a few minutes.
- Leadership gets every comparison view each month, not just when there is time.
- Cause-structure-over-time turns scrap from a number into a trend you can act on.
- A checking view means the totals are trusted.
We design and deploy to the ISO/IEC 27001 (information security) and ISO/IEC 42001 (AI management system) frameworks. Data stays where it should, decisions that carry real cost keep a human in the loop, and every model call is logged for audit.
Designed and deployed to these frameworks. Not a certification claim.
Have a problem like this?
Bring your messiest operational problem. In 30 minutes we will tell you where AI would pay back fastest, and where it would not.
Discuss an operations problem