In semiconductor manufacturing, the success of multi-layer lithography depends on one thing: precision overlay. A nanometer-scale misalignment can trigger a cascade of failures, shorts, opens, or pattern mismatch. Traditional overlay systems, though reliable, are static and can miss real-time deviations.
AI-powered Alignment and Overlay Accuracy solutions use real-time computer vision to detect and correct misalignment during lithography. By continuously comparing new patterns with reference layers, AI vision ensures every overlay falls within strict tolerances, even on advanced nodes.
This reduces overlay-related yield loss, cuts rework cycles, and ensures multi-patterning integrity.
At advanced nodes (5nm/3nm), even tiny overlay shifts can cause electrical shorts or performance drift.
Thermal expansion or tool wear causes gradual shifts that traditional static calibration can’t catch.
Without real-time feedback, overlay errors often go unnoticed until after etching or metrology.
Multiple exposure passes increase the chance of cumulative misalignment, especially on dense layers.
Computer vision verifies overlay precision during exposure, not just in post-processing.
AI models trained to identify and measure overlay deviation at single-digit nanometer tolerances.
Learns and predicts overlay drift based on historical tool movement, exposure conditions, and material response.
Feeds deviation data into stepper/aligner systems for automatic compensation and dynamic realignment.
We begin by integrating CAD-based reference layers or GDSII data to set visual baselines for overlay comparison.
Specialized cameras with nanometer resolution are installed near lithography tools. Calibration includes pixel-level correction and motion compensation for fast-moving wafer stages.
Using archived mismatch incidents, our AI is trained to distinguish between acceptable variation and true overlay faults across complex geometries and resist layers.
As patterns are exposed, real-time visual feedback is compared to reference alignment. Detected deviation values are immediately sent to the scanner or aligner system for correction during the same pass.
Stay updated with the trending and most impactful tech insights. Check out the expert analyses, real-world applications, and forward-thinking ideas that shape the future of AI Computer Vision and innovation.
Some achievements do not arrive with loud announcements or dramatic celebrations. They arrive quietly, almost gently, carrying a kind of weight that only people close to the work fully understand. WebOccult’s Best Paper recognition at the IEEE was one such moment. Out of more than 450 research papers submitted from across the world, only five […]
CEO & Co-founder
People usually don’t think about logistics until there’s a delay in order delivery. On the other hand, there are millions of products that move across borders every single day, as their journey includes going through different ports, warehouses and distribution centres before the product reaches its respective owner. So there’s a lot that happens behind […]
CEO & Co-founder
When we discuss the ways to improve quality in factories today, one solution that often comes up is Computer Vision in manufacturing. Supervising a production line makes it clear how easily small issues can go unnoticed. A small crack, a misplaced center label, or a missing screw may seem irrelevant, but these small problems can […]
CEO & Co-founder