Sistemas de visão aplicados em processos de qualidade automotiva: Uma revisão sistemática

Abstract

The automotive industry produces millions of vehicles annually, making it a vital sector globally. Inspection processes, including visual checks and computer vision systems, ensure product quality and safety. Recent advances in machine learning and computer vision techniques have propelled the use of computer vision systems for automotive inspection. These systems enhance efficiency and production quality by detecting defects and anomalies missed by human operators. To gain a current understanding and identify relevant scientific research on automotive inspection using computer vision and machine learning, a systematic review titled "Computer Vision Systems Applied in Automotive Quality Processes" analyzed the Web of Science database. Initially, 220 articles were found, but after applying filters, 16 works were selected. The study employed semantic network analysis to identify inspection trends and examined patents and software records. This research aims to consolidate, organize, and update scientific knowledge in this field while assisting decision-making and serving as a reference for other researchers.