From above of assorted plastic cups with coffee chaotically scattered on top on beige surface

SolVisionCase Study

Coffee Capsule Inspection Using AI

Case

Efficiency and Precision in Coffee Capsule Packaging

Coffee capsule machines have become increasingly popular, providing a variety of coffee blends in disposable capsules. These capsules are often color-coded to indicate their origin, flavor profile, and coffee type. In automated packaging systems, the precise classification and placement of each capsule into designated positions within tray packaging are crucial for ensuring correct contents and maintaining production quality.

Challenge

Colored Aluminum Packaging Recognition

The diverse range of coffee capsules often features subtle variations in color that can be difficult to differentiate, even for advanced AI systems. The reflective nature of aluminum packaging creates glare, complicating image recognition and obscuring these distinctions. Traditional rule-based vision systems rely on specific lighting, lenses, and sensors to achieve accurate inspection; however, they often struggle with reflective surfaces and varying environmental conditions, leading to inefficiencies in the packaging inspection process.

Solution

Precision AI Inspection with SolVision

SolVision enhances the classification of coffee capsules in tray packaging through advanced AI-driven inspection. It recognizes both standard and irregular placement patterns, allowing for accurate classification and real-time detection of misaligned capsules. With its presence/absence detection capability, SolVision ensures that every capsule is accounted for. By utilizing diverse training images, it effectively addresses challenges from reflective aluminum packaging and subtle color variations, ensuring high detection accuracy and consistent product quality

Coffee Capsule Presence/Absence Detection

Coffee capsule testing case

Missing Capsule

Coffee capsule testing case

Incorrect Sequence

Outcome

Improved inspection accuracy for consistent quality
Excelled at detecting reflective materials, reducing errors
Streamlined operations with precise sequence identification