Automation in manufacturing improves efficiency, safety, and product quality. YOLOvX enables real-time defect detection, worker safety monitoring, and robotic process automation. Traditional manual counting isn’t just time-consuming – it’s costing manufacturers thousands in human errors, production delays, and inventory discrepancies. In fast-paced operations, even a small miscalculation can create major ripple effects downstream.
Problem statement
Manufacturing and quality control suffer from manual inspections, production inefficiencies, and undetected defects, leading to waste and delays. AI-powered computer vision enables real-time defect detection, process automation, and precision monitoring, ensuring higher efficiency and product quality.
Application
- Defect Detection on Assembly Lines: Identifies faulty products, reducing waste.
- Worker Safety Compliance: Ensures workers wear safety gear like helmets and gloves.
- Robotic Process Automation: Helps robotic arms in sorting, assembling, and packaging.
Usecase
Computer Vision Yarn Counter system
This solution uses computer vision technology to automatically track and count yarn spools as they cross a detection line. The system:
- Delivers high counting accuracy
- Operates 24/7 without fatigue
- Provides real-time inventory updates
- Eliminates manual counting errors
Biscuits Alignment with AI-Powered Quality Control
Ensuring precise alignment of biscuits during the packaging process is a constant challenge, impacting both product quality and visual appeal.
Leveraging the vision technology to tackle this issue head-on, which utilizes Oriented Bounding Boxes (OBB) to meticulously analyze biscuits alignment.
Benefits
- Increases production efficiency with automated quality checks.
- Enhances workplace safety by detecting safety violations.
- Reduces manufacturing defects, improving product reliability.
