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Visual Quality Detection

Visual quality detection automates the analysis of products on the production line or equipment in production facilities for quality control using machine vision. Machine vision is the technology and methods used to provide image-based automatic inspection. It is a system that uses visual computing technology to mechanically “see” the activities that take place one by one along the production line. The components of an automatic inspection system usually include lighting, a camera or other image acquiring device, a processor, software, and output devices. Machine vision surpasses human vision at the quantitative and qualitative measurement of a structured scene because of its speed, accuracy, and repeatability. A machine vision system can easily assess object details too small to be seen by the human eye, and inspect them with greater reliability and lesser error. On a production line, machine vision systems can inspect hundreds or thousands of parts per minute reliably and repeatedly, far exceeding the inspection capabilities of humans. It also uses Artificial Intelligence to mimick human level intelligence to distinguish anomalies, parts, and characters, while tolerating natural variations in complex patterns. It merges the adaptability of human visual inspection with the speed and reliability of a computerized system.

  • Automotive
  • Discrete Manufacturing
    Product Development
    Quality Assurance
  • Beckhoff: Fully Automated Visual Inspection System
    Tofflon has developed a fully automatic machine that uses light to inspect vials, medicine bottles, or infusion containers for glass fragments, aluminum particles, rubber grains, hairs, fibers, or other contaminants. It also detects damaged containers with cracks or inclusions (microscopic imperfections), automatically removing faulty or contaminated products. In order to cover all production processes for freeze-dried pharmaceuticals, Tofflon needed to create an open, consistent, and module-based automation concept.
    Adapt-N: 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.
    Mesh Systems: Remotely Control, Monitor and Manage Lighting Systems
    Intermatic needed a solution to help their customers drastically reduce costs associated with making sure all billboard lights were on and working properly. The traditional method was costly, time consuming and inefficient as may billboards are located in isolated regions.
  • The overall machine vision market is expected to grow from USD 8.12 billion in 2015 to USD 14.43 billion by 2022, at a CAGR of 8.15% between 2016 and 2022.

    Source: Markets and Markets


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