Emerging Trends and Applications of Machine Vision in Industrial Automation
Publish place: 16th International Conference on Mechanical, Construction Industrial & Civil Engineering
Publish Year: 1403
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
MMICONF16_030
تاریخ نمایه سازی: 13 شهریور 1403
Abstract:
Machine vision technology has become a cornerstone in the automation of production processes, providing unprecedented improvements in precision, efficiency, and safety. This paper explores the critical importance of machine vision in modern manufacturing, outlining its diverse applications, including quality control, object recognition, assembly verification, and robot guidance. The goals of employing machine vision—improving product quality, minimizing waste, ensuring consistency, and enhancing safety—are thoroughly examined, alongside the tangible effects such as cost reduction, improved operational efficiency, and enhanced competitiveness. Additionally, future trends such as the integration of AI and machine learning, advances in imaging technology, and predictive maintenance are discussed, highlighting the potential for further evolution in this field. Machine vision systems utilize advanced imaging technologies and sophisticated algorithms to analyze visual data and make informed decisions, surpassing human capabilities in speed and accuracy. The integration of AI enables these systems to adapt to changing environments and learn from vast datasets, enhancing their ability to perform complex tasks autonomously. Advances in imaging technology, including high-resolution cameras and ۳D vision systems, continue to expand the capabilities of machine vision, allowing for more detailed inspections and precise measurements. Predictive maintenance techniques leverage data analytics to predict equipment failures before they occur, optimizing operational efficiency and reducing downtime. This comprehensive review consolidates existing knowledge and provides a roadmap for future research and development in machine vision and automation, emphasizing the transformative impact of these technologies on industrial processes and highlighting opportunities for innovation and advancement.
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Authors
Parsa Asasi Moghaddam
M.sc Student of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
Zahra Maher
M.sc Student of Industrial Management, University of Tehran, Tehran, Iran