Defect Monitoring

Revolutionising Quality Control with AI-Powered Defect Detection

A leading global alcohol beverage company transformed their quality assurance process, achieving 99% accuracy in detecting critical defects through innovative startup-driven solutions to solve manual inspection issues creating significant operational challenges.

Key Objectives

  • Automate inspection of liquids, bottles, closures, labels, and packaging.
  • Improve accuracy, consistency, and scalability of defect detection across SKUs.
  • Enhance real-time visibility into defect trends and enable full coverage.
  • Reduce wastage through early defect identification.
  • Establish scalable systems for multi-plant rollout and operational efficiency.
  • Ensure consistency and compliance across all the plants.

OpenI Advantage

The OpenI team architected the solution by combining multiple innovative solutions. Leveraging its global startup ecosystem, OpenI identified and deployed cutting-edge emerging technologies:

  • High FPS cameras to capture moving products on the conveyor belt
  • AI-powered edge computing for real-time defect detection and categorisation
  • Robotic automation enabling 360° product analysis

The challenge was launched on the OpenI platform engaging startups, VCs, and accelerators worldwide to scout for the right solutions.

defect monitoring case study images

99%

Detection Accuracy

Critical defect identification rate achieved through AI integration

360°

Coverage

Complete bottle inspection with high-resolution cameras

100%

Automation

Fully automated in-line quality control system

Key Advantages of AI-Powered Quality Control

Real-time Defect Interception

Immediate detection of defects prevents compromised products from reaching the market, ensuring consistently high quality standards and consumer safety.

Scalable Modular Design

The system's flexible architecture allows for seamless integration and expansion, adapting effortlessly to increasing production volumes and diverse product lines.

Reduced Rework & Recalls

Minimising errors early in the production cycle significantly cuts down on rework costs and safeguards brand reputation by preventing costly product recalls.

Reduced Manual Dependency

Automating routine inspections frees human operators to focus on complex problem-solving and strategic oversight, boosting overall operational efficiency and accuracy.

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