{
  "patent_number": "US 12243216",
  "country": "US",
  "title": "How AI Cameras Check Factory Parts for Flaws",
  "original_title": "System and method for AI visual inspection",
  "summary": "This patent describes an automated system using a camera and artificial intelligence to inspect manufactured parts, identifying defect types, locations, and confidence levels, then communicating this data to a factory controller.",
  "what_it_does": "The system uses a camera to capture images of a manufactured item (Claim 1). A 'node computing device' then analyzes these images using a specialized AI model, specifically a machine-learning based object detection model (Claim 1). This model is trained to spot various types of flaws, like a scratch or a dent, and can classify them into three or more categories (Claim 1). It outputs 'defect data' which includes the type of defect, its exact location, and how confident the AI is about its finding (Claim 1). This defect data is then sent to a 'programmable logic controller' (PLC), which is a computer that controls factory machinery (Claim 1). For example, if inspecting a car part, the system could take pictures, identify a specific crack, and then tell the PLC to reject that part. The system can also use a robotic arm to move the camera (Claim 3) or rotate the part being inspected (Claim 4) to get a full view, and can even stitch multiple images together for a complete picture (Claim 5). It can also confirm a defect by tracking it across multiple image frames before reporting it (Claim 7).",
  "what_it_does_not_cover": [
    "Does not cover visual inspection systems that use traditional rule-based computer vision instead of a machine-learning based object detection model.",
    "Does not cover systems that only classify defects into fewer than three categories or detect only a single type of defect (Claim 1).",
    "Does not cover systems where the AI output lacks specific defect class, location, and a confidence level (Claim 1).",
    "Does not cover systems where the AI output is not sent to a programmable logic controller (PLC) for factory automation (Claim 1).",
    "Does not cover manual human inspection processes, as it specifies an automated AI system."
  ],
  "filed": "2020-09-30",
  "granted": "2025-03-04",
  "expires": "2040-09-30",
  "status": "active",
  "holder": "Musashi Auto Parts Canada",
  "holder_url": "https://patentbrief.org/company/musashi-auto-parts-canada",
  "inventors": [
    {
      "name": "Raef Shehata",
      "url": "https://patentbrief.org/inventor/raef-shehata"
    },
    {
      "name": "Martin Bufi",
      "url": "https://patentbrief.org/inventor/martin-bufi"
    }
  ],
  "times_cited": 0,
  "tags": [
    "manufacturing",
    "ai_ml",
    "robotics",
    "industrial_automation",
    "quality_control",
    "automotive",
    "consumer_electronics"
  ],
  "abstract": "Provided is a system and method for visual inspection. The system may be used in a quality assurance station at a manufacturing facility or site. The system may evaluate and determine the quality of manufactured or fabricated articles. The system may include a mechanical subsystem for capturing images of the article. The system may include a sensor such as a camera for capturing data, such as images. The system may include an artificial intelligence system to determine if the article suffers from an impermissible defect.",
  "url": "https://patentbrief.org/patent/us/12243216/system-and-method-for-ai-visual-inspection",
  "markdown_url": "https://patentbrief.org/patent/us/12243216/system-and-method-for-ai-visual-inspection/md",
  "google_patents_url": "https://patents.google.com/patent/US12243216",
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}