# Predictive Quality Control with AI

Quality control has evolved through three eras. Reactive quality (inspect and reject) catches defects after they are made. Statistical process control (SPC) monitors process variation to detect when something is drifting out of specification. Predictive quality uses AI to identify the conditions that lead to defects before those defects occur.

The Economics of Prediction vs. Detection

The cost multiplier for defects follows a well-known pattern. Catching a defect at the workstation costs 1×. Catching it at end-of-line inspection costs 10×. Catching it after shipping costs 100×. A warranty return or field failure can cost 1,000× or more when you include logistics, reputation damage, and regulatory consequences.

Predictive quality control aims to catch the defect at 0.1× — before it exists. The savings compound: no scrap, no rework, no inspection time wasted, no customer impact.