The Vision AI Center of Excellence Blueprint
A playbook for turning vision AI into an owned, scalable capability.
Add a real-time inspection layer to every die attach with vision AI for die attach inspection. Built for the packaging floors where the joint under the die is the thermal path the whole device depends on, a fillet's height around four die edges is the only visible evidence of what's underneath, and the epoxy that bled two hundred microns too far costs a bond wire at the next station. Whether you're dispensing epoxy, placing die, or attaching power die with solder and sintered silver, Roboflow inspects every die, fillet, and substrate at line rate, with per-lot records behind every device.
Die Placement and Condition:
Epoxy, Solder, and Fillets:
Lines, Stations, and Systems Integration:
Bring intelligence to every die attach today. Stop attach defects from becoming hot spots at full power, bonder yield mysteries, or the field return that ends at an uninspected interface.
What is die attach inspection with Vision AI?
Die attach inspection with vision AI uses computer vision models to inspect the die attach process through dispense, placement, and cure: die placement, rotation, and edge condition, epoxy fillet coverage and height along every die edge, bleed toward bond pads, contamination, and solder and sintered silver coverage on power die. Models trained on your actual devices inspect every unit at line rate, with per-lot records that support MIL-STD-883, AEC-Q100, and IATF 16949 documentation.
Can Vision AI judge epoxy fillets and bleed?
The fillet is a judgment case, not a measurement case: a bead of epoxy whose height and continuity along four die edges is the visible evidence of the joint underneath, bleed that's a translucent film a few microns thick on a reflective substrate, and a tilt of a fraction of a degree that shows up only as fillet asymmetry. Deep-learning models trained on your actual devices, materials, and lighting learn what a healthy fillet looks like on each package, flag starved edges, flooding, bleed, and asymmetry, hold that judgment across dispense patterns and die sizes, and route uncertain units to review instead of guessing, on every device rather than an operator's sample.
Does this replace X-ray and acoustic microscopy?
No. X-ray and scanning acoustic microscopy keep owning what's under the die: voiding, delamination, and coverage at the bond line, and shear testing keeps the destructive strength record. Vision AI adds the visible layer those tools don't run at line rate: fillet coverage on every edge of every die, bleed caught before it reaches a pad, placement, rotation, and chipped edges, all upstream of cure while rework is still possible. Subsurface findings and visual findings land in the same per-lot record, and a starved-fillet trend usually reaches the dispenser before the SAM queue sees the void.
Can it integrate with our die bonders, factory hosts, and MES?
Yes. Roboflow Inference exposes a standard API and supports common industrial protocols, so die attach inspection events flow into your existing systems: die bonder and dispense station controllers, factory hosts alongside SECS/GEM equipment integration, MES and ERP platforms like SAP and Oracle, and SCADA and HMI platforms like Ignition and AVEVA, through REST, MQTT, OPC UA, and direct database writes. PLC-level integration holds a magazine or routes a substrate the moment a check fails, and every event carries lot, device, station, imagery, and disposition, with a full audit trail behind every shipment.
