自动化
质量保证
金属薄板
制作
机器视觉
计算机科学
质量(理念)
工程类
计算机视觉
人工智能
制造工程
工程制图
机械工程
运营管理
医学
物理
外部质量评估
量子力学
病理
替代医学
作者
S. Pratheesh Kumar,N. Balasubramanian
标识
DOI:10.1142/s0219686724500392
摘要
This review emphasizes the evolving need for automated inspection in metal fabrication processes due to the increasing complexity of design advancements over the years. The study explores various defect detection algorithms and evaluates their effectiveness in enhancing the accuracy and reliability of the inspection process. Machine vision plays a crucial role in this context, contributing significantly to the precision of the inspection process in metal fabrication. Its ability to handle complex tasks ensures a thorough assessment of manufactured components. The paper also explores the use of digital image correlation (DIC) as a key tool in quality assurance for metal fabricated products. This technique provides detailed insights, enabling a thorough understanding of structural integrity and defect identification. By integrating insights on automated inspection through defect detection algorithms, machine vision and DIC, this review aims to advance quality assurance methodologies in the ever-evolving field of metal fabrication.
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