From Hours to Minutes: AI-Powered PCB X-Ray Inspection for Vinyas

From Hours to Minutes: AI-Powered PCB X-Ray Inspection for Vinyas

An AI inspection pipeline is replacing manual BGA void detection with target full-board inspection in under 10 minutes.

<10 minTargeting <10 min inspection, >97% ball detection, <2% void error

For Vinyas Innovative Technologies, ITChamps is building an AI pipeline on top of Nordson Quada 3 infrastructure to automate BGA localization, solder-ball detection, void measurement, and traceable report generation.

The Challenge

Manual BGA X-ray inspection was too slow and structurally incomplete

The existing workflow depended on operators to navigate BGAs, mark shadow-zone balls, estimate voids, and manually log outcomes, creating throughput, consistency, and traceability problems.

  • A single PCB inspection consumed hours of skilled operator time.
  • The Quada 3 semi-auto workflow missed shadow-zone solder balls entirely.
  • Void estimation was subjective and varied between operators.
  • Inspection data lacked automated traceability and searchable reporting.
  • Throughput scaled with headcount rather than capability.

The Solution

An AI pipeline layered onto existing Nordson Quada 3 hardware

The system detects BGA locations, identifies all solder balls including occluded ones, segments voids, classifies pass/fail against IPC-7095D thresholds, and automatically generates traceable reports.

01BGA Localisation

YOLOv8 and Grounding DINO detect and map all BGA locations from X-ray images.

02Full Ball Detection

SAM 2 and a Vision Transformer identify all balls, including shadow-zone cases the native system misses.

03Void Classification

U-Net and PatchCore segment void regions and calculate precise void percentages against IPC-7095D thresholds.

04Automated Reporting

The pipeline generates PDF and Excel reports linked to serial numbers, dates, and operators in a searchable quality database.

Results

Measured business impact

<10 minTarget inspection cycle

Full PCB inspection target from a current baseline of several hours.

>97%Target ball detection

Coverage target includes shadow-zone balls missed by the current workflow.

<2%Target void measurement error

Planned accuracy target comparable to dedicated AXI systems.

ZeroTarget manual involvement

The design aims to eliminate manual marking, detection, and report generation.

Highlights

  • Implementation is currently in progress for April to September 2026.
  • No new X-ray hardware replacement is required.
  • The design supports IPC-7095D-compliant traceable reporting.
  • The system is intended to create a searchable quality intelligence database.

Services and technology

Computer Vision AutomationQuality Inspection AIManufacturing AnalyticsYOLOv8Grounding DINOSAM 2Vision TransformerU-NetPatchCore

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