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视觉质量检测
概述
视觉质量检测可自动分析生产线上的产品或生产设施中的设备，以使用机器视觉进行质量控制。机器视觉是用于提供基于图像的自动检测的技术和方法。它是一个使用视觉计算技术机械地“看到”沿生产线发生的活动的系统。自动检测系统的组件通常包括照明、照相机或其他图像采集设备、处理器、软件和输出设备。由于其速度、准确性和可重复性，机器视觉在结构化场景的定量和定性测量方面超过了人类视觉。机器视觉系统可以轻松评估人眼无法看到的物体细节，并以更高的可靠性和更少的错误对其进行检查。在生产线上，机器视觉系统每分钟可以可靠且重复地检测成百上千个零件，远远超过人类的检测能力。它还使用人工智能模仿人类水平的智能来区分异常、部分和字符，同时容忍复杂模式中的自然变化。它将人工视觉检查的适应性与计算机系统的速度和可靠性相结合。
适用行业
- 汽车
- 运输
适用功能
- 离散制造
- 产品开发
- 质量保证
市场规模
案例研究.
Case Study
Diverse N Management Practices Generate Value to Farmers
Shannon Gomes, owner of Cedar Basin Corp Consulting, has long been searching for a better way to monitor nitrogen (N) available and provide precise N recommendations. He has tried "all the different nitrogen management tools", with varying results, but has never been satisfied. He is looking for a real-time, location-specific adaptive N recommendation model that accounts for weather, management practices, and field variability.
Case Study
8x increased productivity with VKS
Before VKS, a teacher would spend a lot of time showing a group of 22 students how to build a set of stairs within a semester of 120 hours. Along with not leaving the teacher much time to provide one-on-one support for each student to properly learn carpentry, it also left a considerable amount of room for error. Key information would be misinterpreted or lost as the class was taught in the typical show-and-tell way.
