<p>The manufacturing sector faces numerous challenges, including labour shortages, safety concerns, and the need for increased efficiency and precision. Machine vision technology has emerged as a crucial solution to these issues, offering advanced tools for automated inspection, quality control, robotic guidance, predictive diagnostics, and safety compliance. This comprehensive review of machine vision applications in manufacturing over the past five years focuses on the integration of advanced digital technologies and automation. The study systematically analyses 79 research papers and explores current trends, unresolved issues, and future research directions in the domain of machine vision. This review emphasises the importance of machine vision in enhancing manufacturing processes, its role in mitigating industry challenges, and the potential for further advancements through interdisciplinary research. By providing critical insights into the capabilities and limitations of current systems, it can inform future innovation in machine vision and manufacturing automation.</p>

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A Systematic Review of Machine Vision Applications in Factory and Manufacturing Processes: From Quality Control to Predictive Diagnostics

  • Seongje Kim,
  • Thong Phi Nguyen,
  • Jonghun Yoon

摘要

The manufacturing sector faces numerous challenges, including labour shortages, safety concerns, and the need for increased efficiency and precision. Machine vision technology has emerged as a crucial solution to these issues, offering advanced tools for automated inspection, quality control, robotic guidance, predictive diagnostics, and safety compliance. This comprehensive review of machine vision applications in manufacturing over the past five years focuses on the integration of advanced digital technologies and automation. The study systematically analyses 79 research papers and explores current trends, unresolved issues, and future research directions in the domain of machine vision. This review emphasises the importance of machine vision in enhancing manufacturing processes, its role in mitigating industry challenges, and the potential for further advancements through interdisciplinary research. By providing critical insights into the capabilities and limitations of current systems, it can inform future innovation in machine vision and manufacturing automation.