Method and process for automated auditing of inline quality inspection

Abstract

A method and system for implementation of quality control includes a machine vision system for capturing images of instances of a product, and a computer system including computer memory containing machine-readable instructions executable by a processor. The processor evaluates the quality control images for a plurality of potential quality defects in the product and generates a defect alert associated with a captured image in which at least one potential quality defect is identified. Information about each defect alert is stored in a database log file in the computer memory. A neural network machine learning algorithm processes the database log file by, in a learning phase, receiving human-initiated input accepting or rejecting each defect alert and storing the human-initiated input in the log file, and, in an automated phase, automatically accepting or rejecting at least some defect alerts without performing the step of receiving human initiated input.