Quality calculator

Cost of Poor Quality Calculator

Roll internal and external quality losses into a simple total cost and per-unit impact.

What this calculator does

  • Combine scrap, rework, warranty, inspection, and customer penalty costs into one quality-loss number.
  • Use when quality issues need financial priority for corrective action or improvement work.
  • Combine scrap, rework, warranty, inspection, and customer penalty costs into one quality-loss number.

Formula used

  • COPQ = scrap + rework + warranty + inspection + penalties
  • Internal failure cost = scrap + rework
  • COPQ per shipped unit = COPQ รท shipped units

Inputs explained

  • Scrap cost: undefined
  • Rework cost: undefined
  • Warranty cost: undefined
  • Inspection / containment cost: undefined
  • Customer penalties: undefined
  • Shipped units: undefined

How to use the result

  • Use when quality issues need financial priority for corrective action or improvement work.
  • This is a planning calculator. Validate assumptions against your process data before using the result as a final quote, schedule, or engineering decision.

Common questions

  • Which inputs usually drive the cost of poor quality result? scrap cost, rework cost, warranty cost, inspection / containment cost, customer penalties, and shipped units usually have the biggest effect. When one of those assumptions changes, rerun the calculator and compare the new $ result before updating the plan.
  • What does the cost of poor quality calculator do? Combine scrap, rework, warranty, inspection, and customer penalty costs into one quality-loss number.
  • What inputs do I need for the cost of poor quality calculator? You need scrap cost, rework cost, warranty cost, inspection / containment cost, customer penalties, and shipped units. Use measured values from your line, quote package, supplier data, or current production plan whenever possible.
  • How should I interpret the cost of poor quality result? Treat the $ output as a planning estimate for quality work. Compare it against process history, quoted assumptions, and operating limits before making final decisions.

Last reviewed 2026-05-12.