"Using AI for Quality Control: How Relimetrics is Making Zero Defects a Reality"


Staff member
May 18, 2022
Making Zero Defects a Reality: A Relimetrics Case Study

In an era where businesses thrive or fail based on the quality of their products, the goal of zero defects in manufacturing has become a critical target. With the advent of computer vision and machine learning, companies can transform their quality management. This post explores how Relimetrics, a German tech firm, uses these technologies to help businesses analyze video data in real-time and bring them closer to achieving zero defects.

The Challenge
With increased demand for product customization, manufacturing and assembly complexities have grown, raising the potential for anomalies. A single defect could result in significant recalls, costing billions of dollars and damaging the manufacturer's reputation. The solution to this challenge lies in digitizing quality audit cycles and improving defect detection accuracy.

The Solution: Real-Time Video Analytics and Machine Learning
Relimetrics, partnering with HPE OEM and NVIDIA Metropolis, developed a transformative software solution. Their technology leverages GPU-accelerated video analytics and machine learning, significantly improving defect detection accuracy by deploying the solution directly on the shop floor.

The Results
By enabling companies to run video analytics at the edge, Relimetrics helps them detect quality issues more accurately and address them quickly. This strategy has brought companies closer to achieving zero defects, improving profitability through reduced scrap and rework, and increasing customer satisfaction and retention.

In a case study, Relimetrics digitized the QA of a Foxconn production line where servers for Hewlett Packard Enterprise (HPE) are manufactured. This resulted in a 25% reduction in defective products reaching customers, a 20% expansion in test coverage, and a 96-second reduction in inspection time per server. This transformation showcases how edge computing, real-time video analytics, and machine learning can make the dream of zero defects a reality.