Weighing, Dosing & Loss-in-Weight Feeding worked example

Quality Loss Cost at 92% cost-capture factor: a worked example

This scenario runs the quality loss cost calculation on the strong side: 92% cost-capture factor, with every other input held at its documented default. Use it when quality loss cost in weighing, dosing and loss-in-weight feeding is being put through a weighing, dosing and loss-in-weight feeding weighted-cost review.

The inputs for this scenario

  • Off-spec doses produced: 100 units (unchanged)
  • Cost per off-spec dose: 45 $ / unit (unchanged)
  • Cost-capture factor: 92 % (raised for this scenario; the documented default is 80)
  • Fixed investigation and rework cost: 250 $ (unchanged)

Working through the calculation

  • Applying the documented formula (Quality Loss Cost cost = quantity × rate × capture factor + fixed cost) to the inputs above produces each figure below.
  • At this operating point the engine returns 4,390 $ for weighted cost, the number this scenario is built around.
  • At this operating point the engine returns 43.9 $ / piece for per piece value.
  • At this operating point the engine returns 4,140 $ for captured value.
  • At this operating point the engine returns 250 $ for fixed adjustment.

How this compares with the baseline

  • Against the tool's baseline example, where cost-capture factor sits at 80% and the headline result is 3,850 $, this scenario comes in 14.03% above the baseline at 4,390 $.
  • Use it to price a batch of off-spec doses or to justify a feeder or tolerance improvement against a known scrap rate. Treat this as a target state: the delta against the baseline quantifies what the improvement is worth before you commit to chasing it.

Results at a glance

  • Weighted cost: 4,390 $ (headline result)
  • Per piece value: 43.9 $ / piece
  • Captured value: 4,140 $
  • Fixed adjustment: 250 $

Run it with your numbers

  • Every input above is editable in the live Quality Loss Cost calculator, which recalculates instantly and can be shared with the inputs intact.

Last reviewed 2026-05-12.