Food and Beverage
The food and beverage industry faces significant challenges in visual inspection due to diverse packaging materials and surface interference like oil or condensation, which hinder the detection of sub-0.1mm defects. Custom algorithms for different packages require lengthy development, high costs (US$70,000–140,000 each), and are difficult to maintain. High-speed production demands millisecond responses, yet motion blur and lighting variations disrupt image quality. With varying products, strict requirements, and complex environments, applying AI visual inspection efficiently remains highly challenging.
Aqrose AI Solution Overview
Aqrose Technology provides AI-powered visual inspection solutions for the food and beverage industry , utilizing its AIDI software and deep learning to detect defects as small as 0.5mm—such as spots, burns, and cracks—in products like quail eggs and instant noodles. The system ensures high-speed, accurate inspection under complex conditions, reducing manual effort and improving quality control for smarter manufacturing.
Full-process Inspection of Food and Beverage Industry
Food
Beverage
Success Cases
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The visual inspection of quail eggs primarily involves detecting defects such as cracks, stains, blood spots, exposed yolk, and shell residue. Currently, this process largely relies on manual visual inspection, which is inefficient and prone to fatigue, resulting in high rates of missed defects and -
Currently, the appearance inspection of instant noodle cakes is crucial in high-speed automated production lines, yet it faces numerous challenges. Production lines operate at extremely high speeds, requiring the detection of defects as small as 0.5mm, such as oil residue, dark spots, and burnt resi -
Seal inspection is vital to food safety and quality. In actual production, critical defects such as contamination in seals, unsealed packages, and partially sealed packages often occur. Since food packaging is typically made of flexible plastic and incoming materials on production lines vary in orie -
In the food industry, during product grading based on weight, shape, and other criteria, workers often forget to weigh items or lack accuracy in evaluating shapes. This leads to high costs and significant losses in product grading. To resolve this, our team implemented VAS (Video Analytics System)
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