Cost of Quality Assessment
20
Calculate the total cost of quality by combining inspection appraisal costs and the external failure costs from missed defects.
NOTEAbout This Model
## Calculate the total cost of quality by combining inspection appraisal costs and the external failure costs from missed defects. This model estimates **Total Quality Cost** based on uncertain inputs: Defect Rate, Inspection Effectiveness, Cost Of Poor Quality Per Defect, Cost Of Inspection Per Unit. Fixed values: Production Volume. Run the simulation to see the distribution of possible outcomes.
CONSTANTProduction Volume
10000
Total units produced in the period.
production_volume
VARIABLEDefect Rate
beta(2, 18.9)
Typical manufacturing defect rates range from 1% to 10%.
defect_rate
VARIABLEInspection Effectiveness
beta(14.9, 5.1)
Probability that a defect is caught by the current inspection protocol.
inspection_effectiveness
VARIABLECost Of Inspection Per Unit
triangular(0.5, 2.75, 5)
Incremental cost to inspect a single unit.
cost_of_inspection_per_unit
VARIABLECost Of Poor Quality Per Defect
triangular(100, 550, 1000)
Financial impact of a defect reaching a customer including returns and reputation.
cost_of_poor_quality_per_defect
FORMULATotal Defects
production_volume * defect_rate
Number of defective units produced.
total_defects
FORMULAEscaped Defects
total_defects * (1 - inspection_effectiveness)
Defects missed by inspection and reaching the customer (external failure).
escaped_defects
FORMULATotal Quality Cost
(production_volume * cost_of_inspection_per_unit) + (escaped_defects * cost_of_poor_quality_per_defect)
Sum of inspection costs (appraisal) and costs from failed units reaching the customer (external failure cost).
total_quality_cost
OUTPUTTotal Quality Cost
total_quality_cost
Total cost of quality combining prevention, appraisal, and failure costs. An optimal quality program minimizes total cost—not just defects. Higher inspection spend should reduce failure costs.
What is Carlo?
Carlo is a visual tool for Monte Carlo simulation. Model uncertainty by dragging probability distributions, connecting them visually, and running thousands of scenarios instantly.