Use-Case: Semiconductor Manufacturer
How FireVisor helps to save 100,000 man hours per machine for a large wafer manufacturer
Semiconductor manufacturing is a huge market and one of the most competitive in the industry.
Challenges In The Semiconductor Industry
Constant need for innovation
Semiconductor manufacturers need to continuously innovate to stay relevant/competitive as products have very short life cycles.
High cost of poor quality
With a huge market like the semiconductor industry; the stakes are high, and the margin for error is low. Costs of product recall and order replacements can be devastating to profits and brand image.
Speed is key
As more customers demand products at speed. Semiconductor manufacturers must fully automate production to stay ahead of the competition.
High manpower cost
Specialized tech factories running in Singapore have a very high manpower cost of manual defect detection. Moreover, current manual detection is susceptible to tiredness, time of day, external conditions etc.
AI-based defect detection for self aware factories
AI-based defect detection for self-aware factories
Seemless Integration
Integrates easily with existing inspection systems and wafer handling robots
Repeatable, reliable and robust to line changes
Reliable deep learning-based defect identification, that gives accurate results even if external conditions like light settings vary
Accurate defect identification
Accurately identifies defects, reducing defect escapees and false positives with 98% accuracy
Tailored for the semiconductor industry
Powerful data exploration tools with visual data analytics capability specially tailored for wafer manufacturing
Process
We saved USD 100,000 per machine in man-hour costs
Results
100% OPERATOR TIME SAVED
Manual defect detection no longer needed, with a highly accurate cognitive detection system.
ROBUST, HIGHLY ADAPTABLE
Our system is highly adaptable for product changes, new defect types, and changes in external conditions.
GROUNDWORK FOR ANALYTICS
With highly accurate pixel-by-pixel defect detection, real-time defect analytics becomes easy to implement