Product Inspection Methodology via Deep Learning: An Overview
This work addresses product quality inspection for manufacturing industries, but it appears incremental as it integrates existing methods into a framework without claiming major breakthroughs.
The paper presents a unified framework for product quality inspection using deep learning, detailing model categorization, system integration, and maintenance methods, and verifies effectiveness through performance comparisons in various test scenarios.
In this work, we present a framework for product quality inspection based on deep learning techniques. First, we categorize several deep learning models that can be applied to product inspection systems. Also we explain entire steps for building a deep learning-based inspection system in great detail. Second, we address connection schemes that efficiently link the deep learning models to the product inspection systems. Finally, we propose an effective method that can maintain and enhance the deep learning models of the product inspection system. It has good system maintenance and stability due to the proposed methods. All the proposed methods are integrated in a unified framework and we provide detailed explanations of each proposed method. In order to verify the effectiveness of the proposed system, we compared and analyzed the performance of methods in various test scenarios.