AI-Based Vision Inspection System for Date Code Verification

In the food industry, vision systems are becoming increasingly important as final packaging is automated. Food suppliers found that packers checked the quality of goods before they were packaged; automation meant that the vision system had to take over this function. With the current technological advances, the manufacturers can apply vision system techniques, inspection of labels, and recognition of character to the food industry. This has enabled customers to improve their quality and reduce waste.

OAL is UK's leading food technology company that helps food manufacturers to automate their processes. The automation and robotics used by the company is a boon to the food industry, improving the way food is produced. For more than 25 years, OAL has designed, implemented, and automated engineering solutions. The company has built a unique team of specialists in automation, design, and mechanical and product development that can cover most systems used in a food processing plant. Working together, they have combined the skills and knowledge of stakeholders to make real progress in food processing.

Recently, OAL launched APRIL EYE, the world's first AI-based vision system for date code verification. APRIL EYE combines machine learning and AI to automate the date verification process fully and to eliminate a human operator’s requirement. This decreases the risk of product recalls, and emergency product withdrawals (EPWs) created by human errors on packaging lines, which cost food producers £60-80 million per year in waste products.

Wayne Johnson, OAL Connected Director, comments, "We’ve completely turned vision systems on beverage manufacturers, allowing manufacturers to move to unmanned production, improve traceability and reduce costs across the board.” OAL believes that APRIL EYE will provide those manufacturers with the security they need to do this as it really is a fail-safe solution.

By taking pictures of each product’s date code, the APRIL EYE system can read them back using scanners to ensure that they match the date code programmed for that product. The throughput is increased at speeds of more than 300 packs per minute without compromising product safety. If a date code does not match, the production line stops completely, ensuring that no incorrect labels can be placed in the supply chain, protecting consumers, margins, and brands.