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Packaging & Printing · 2025

Packaging & Printing

-50%
Planning time
78% → 94%
On-time delivery
-42%
Incoming defect rate

Background

A 300M+ RMB/year packaging & printing manufacturer with a complex mix of SKUs, frequent rush orders, and two senior planners carrying the entire schedule in their head.

The Pain

  • **Schedule errors** averaging 30-40% when planners were absent.
  • **Cost estimates** based on rough rules of thumb, leading to either lost bids or margin erosion.
  • **Quality drift** caught too late, after hundreds of units had been produced.

What We Built

A private labor-time prediction model trained on 14 months of historical work orders. Delivered as a FastAPI endpoint integrated into the planning tool. Models retrained monthly on the latest 3 months of data.

Outcomes

|--------|--------|-------|

Daily planning time4 hours2.5 hours
On-time delivery78%94%
Incoming defect ratebaseline-42%

The factory reduced its dependency on two key individuals and lifted OEE by reducing changeover wait time.