In-Sight 2800 Series
Easy-to-use vision system with pre-trained AI for solving basic to intermediate-level processing tasks.
Accurate sorting and classification are key to consistent food quality
In food and beverage production, accuracy counts. A misidentified bottle cap color, the wrong fruit in a yogurt cup, or fewer than the promised dozen donuts can disrupt entire batches, leading to packaging errors, costly downtime, and damage to your brand reputation. As production lines get faster and more complex, manufacturers need high-performance measurement capabilities to accurately assess volume, shape, color, and detect subtle defects – especially on irregular or touching items.
Reliable classification and sortation are vital to ensuring higher yields, reducing waste, and helping manufacturers meet quality standards, deliver high-quality products, and maintain customer satisfaction.
By automating the process with advanced machine vision, food manufacturers can be confident every item is correctly categorized – enabling faster processing, fewer errors, and streamlined operations.
Simplifying food and beverage inspection complexities
On the food production line, quickly identifying traits like color, size, and texture is key to maintaining quality and efficiency, but it’s difficult for traditional machine vision systems to distinguish between acceptable and defective products. Those systems can handle simple tasks like edge detection or counting, but they struggle with more complex challenges such as measuring volume, detecting height variations, and finding subtle surface defects.
Natural variation complicates consistent product grading, as visually imperfect but edible items are often discarded. And manual inspection only adds to the challenge with its susceptibility to fatigue, inconsistency, and limitations in keeping up with fast-moving production lines. Frequent changeovers and packaging errors further increase the risk of costly rework, waste, and downtime.
AI-powered classification and sortation solutions help manufacturers cut through complexity across diverse manufacturing applications:
- Coffee beans: Distinguish between visually similar varietals, as well as natural variations within a single varietal, and reject contaminants (plant matter, pebbles, and other materials), ensuring each blend keeps a consistent flavor profile. New bean? Just upload images to train the system; no coding needed.
- Shelled nuts: Find undamaged nuts in the correct orientation amid irregular shapes and broken pieces, for precise pick-and-place onto chocolates – maintaining product quality, and preventing costly rejects, brand damage, and customer dissatisfaction.
- Cookies: Accurately count and verify cookies by measuring volume, shape, and quantity. Advanced shape detection tools precisely identify separate but touching cookies in containers, ensuring proper portion control.
- Chewing gum inspection: Detect subtle cosmetic defects such as dents and scratches on the smooth, curved surfaces of chewing and nicotine gum so customers receive only high-quality, blemish-free pieces.
Identify, sort and route products with speed and accuracy
AI-powered classification identifies product type, size, and condition, while automated sortation ensures every item reaches the right destination. By improving detection accuracy, manufacturers can also reduce the risk of contaminated or unsafe products reaching consumers, helping prevent costly recalls and foodborne illness outbreaks. Trained on a range of product images, Cognex tools easily handle natural variation, even between visually similar items, and make adding new product types simple.
Supported by a global network of experts and flexible online resources, Cognex helps you enhance product integrity, minimize costly rejects, and deliver consistent quality – package after package.