Mattress, Bedding & Foam Product Assembly worked example

Defect/Rework Cost at 35% throughput loss factor: a worked example

What does the result look like when throughput loss factor reaches 35%? The full calculation is worked below with real intermediate numbers. Use this when quantifying the cost of quality issues for management reviews, justifying investment in inspection stations, or tracking the impact of specific defect types (tape edge failures, stains, foam tears).

The inputs for this scenario

  • Defective units requiring rework: 12 mattresses (unchanged)
  • Average rework cost per unit: 35 $ / mattress (unchanged)
  • Throughput loss factor: 35 % (raised for this scenario; the documented default is 30)
  • Fixed quality overhead: 200 $ (unchanged)

Working through the calculation

  • Applying the documented formula (Direct rework cost = defective units × average rework cost per unit) to the inputs above produces each figure below.
  • At this operating point the engine returns 347 $ for weighted cost, the number this scenario is built around.
  • At this operating point the engine returns 28.92 $ / piece for per piece value.
  • At this operating point the engine returns 147 $ for captured value.
  • At this operating point the engine returns 200 $ for fixed adjustment.

How this compares with the baseline

  • Against the tool's baseline example, where throughput loss factor sits at 30% and the headline result is 326 $, this scenario comes in 6.44% above the baseline at 347 $.
  • A figure at this level is achievable when throughput loss factor is genuinely sustained, not just peaked for a shift. It does not capture downstream costs of defects that escape — warranty claims, returns, or brand damage — so it understates the true cost of quality.

Results at a glance

  • Weighted cost: 347 $ (headline result)
  • Per piece value: 28.92 $ / piece
  • Captured value: 147 $
  • Fixed adjustment: 200 $

Run it with your numbers

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

Last reviewed 2026-05-12.