Product defect management method and system and computer readable storage medium

Abstract

The invention relates to the technical field of computers, and provides a product defect management method, which comprises the following steps that: an algorithm identification unit obtains a picture of a product, identifies the picture based on a preset defect identification model to obtain an algorithm identification result, and stores the picture and the algorithm identification result into a database; the artificial recognition unit obtains a picture with an algorithm recognition result being defective or unrecognizable, provides the picture and the algorithm recognition result for a user for artificial recognition, and collects an artificial recognition result fed back by the user as a defect recognition result of the product; a sampling inspection unit in the defect identification module obtains an algorithm identification result of a preset proportion from the database, forwards the algorithm identification result to an artificial identification unit for sampling inspection, and collects a sampling inspection identification result fed back by the artificial identification unit; and the monitoring module counts the probability of inconsistency with the algorithm recognition result in the manual recognition result and the spot check recognition result, and if the probability exceeds a first preset threshold value, a preset defect recognition model is optimized.

Description

technical field [0001] The present application relates to the field of computer information technology, and in particular, to a product defect management method, system, and computer-readable storage medium. Background technique [0002] At present, the detection of most online AOI (Automated Optical Inspection, automatic optical inspection) equipment is based on traditional image processing algorithms. Although the real-time performance is good and the import is convenient, it is often reckless when dealing with detection targets with complex patterns / textures / backgrounds. The stick is not good, and it is easy to be over-checked or missed. In order to ensure the quality, the factory can only strictly control the algorithm parameters and improve the defect detection rate, and then arrange manpower to re-evaluate the "defective products" that have a large number of over-inspected products determined by the AOI equipment, so as to recover the over-inspected products, and worke...

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Problems solved by technology

[0003] In view of the above problems, in order to reduce the reliance on labor and improve the efficiency of feedback, an embodiment of the present application provides a product defect management method, which is applied to a product defect management system, wherein the system includes a defect identification module and a monitoring module, the method includes the steps: the algorithm identification unit in the defect identification module acquires a picture of the product, identifies the picture based on a preset defect identification model to obtain an algorithm identification result, and combines the picture and The algorithm identification results are stored in the database; the manual identification unit in the defect identification module obtains the pictures whose identification results of the algorithm are defective or unrecognizable, and provi

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