Intelligent Machine Vision Implementation for Production Quality Control

Abstract

The paper presents a quality guarantor solution for modern production enterprises based on the combined use of artificial neural networks within a distributed machine vision platform. The platform includes a set of hardware and software modules for visual technical quality control of production processes. There are presented two typical modules for visual inspection of product external appearance and internal parts, spaces and openings using an endoscope video camera. Digital platform software is built for semantic and statistical processing of Big Data characterizing the state of the technological process. The results of the solution implementation in practice are illustrated by several cases of automated visual control of products, automatic verification of the presence of structural fasteners, automated sorting of products, and inspection of internal surfaces and recognizing of holes. Implementation of quality guarantor architecture and design technique based on covering the production process with the modules of external and internal visual quality control allows improving the quality indicators due to systematic and targeted application of intelligent machine vision.

Keywords

• computer vision
• quality control
• cyber-physical systems
• intelligent quality guarantor