Automated Computer Vision for Food Quality Assurance

Food processing plants rely on speed and consistency to maintain quality. Traditional manual inspection methods on high-speed conveyor belts are not only inefficient but also prone to human error. Computer vision offered a way to modernize quality control.

Industry: Food Processing & Manufacturing

Problem:

Manual inspection of products on high-speed conveyor belts was slow, labor-intensive, and inconsistent. Human error led to inaccurate grading, inefficiency, and quality assurance gaps.

Solution:

A computer vision system was deployed above conveyor belts to automate grading and inspection. Using object detection, the system identified defects while analyzing size and color to ensure accurate classification in real time.

Technology Stack:

• Vertex AI

• Dataflow

• BigQuery

• Cloud Functions

• PyTorch

Impact:

Achieved fully automated grading in under 90 milliseconds per item, eliminating the need for manual inspection. This boosted throughput, improved consistency, and significantly reduced operational costs.