AI AOI machine for PCB, designed in-house

An AI AOI machine for PCB that we build in-house. It checks both sides in one cycle and sorts OK and NG.

Illustration: a PCB conveyor under a scanner arch, a floating board view with a teal box, and green OK and red NG bins.
Inspection accuracy on PCBs
≥95%
Both sides checked, then sorted OK and NG
2 PCB sides per cycle
A mechanical holder flips the board
No robot arm
Camera works with the AI
Any brand
Illustration: operators leaning over PCBs under a lamp, a pile of flagged good boards and one defective board unnoticed.

Why do eyes miss PCB defects?

Operators inspect boards by eye, one side at a time, and tired eyes miss defects. SMT machines flag many good boards.

Illustration: a PCB riding a conveyor under cameras, a mechanical flipper turning it, AI marks on the screen.

INDUSIA inspects and sorts both sides

Cameras and AI check side A, a holder flips the board, side B is checked, then OK and NG are sorted.

Illustration: a finished compact PCB inspection machine with conveyor, flip station, cameras, and separate OK and NG bins.

The PCB inspection machine

  • Both sides, one cycleA mechanical holder flips the board. No robot arm.
  • Sorts OK and NGGood and defect boards go to separate bins.
  • Re-checks SMT flagsClears false calls, only real doubts go to the operator.
  • Operators teach defectsNew defects are added in the Visual Editor.

Three things that set us apart from off-the-shelf AOI.

Not just a smart camera. We unlock three things vendors have kept locked.

Use any camera, as long as it’s high resolution.

The AI lives in our software, not in vendor-locked hardware.

INDUSIA.ai compared with common AOI
AspectINDUSIA.aiCommon AOI
CameraYes: Any high-resolution cameraNo: Vendor’s own camera only
Defect trainingYes: Operator does it on siteNo: Must call the vendor
Loading-unloadingYes: Automatic, both sidesNo: Manual, separate
SupportYes: Local team in BatamNo: Overseas support

Visual Editor: train your own AI on good vs. defect.

Operators mark good and defect areas, then train. No vendor call.

mark, train, test, promote
good region defect regionoperators only, no data scientist

Loading-unloading automation, not just a camera.

One conveyor loads, inspects both sides and sorts. No robot arm.

Clay illustration of the machine: a conveyor, a flip station and the OK and NG bins.
  1. LoadThe PCB enters the conveyor in a carrier.
  2. Inspect side ACamera and AI check the first side.AI inspection
  3. Flip holderTurned mechanically. No robot arm.
  4. Inspect side BThe second side is checked automatically.AI inspection
  5. Unload & sortOK and NG boards are separated.

Already running at PCI Elektronik

Questions and answers

AI AOI machine for PCB: an alternative to dedicated AOI cameras in Indonesia

INDUSIA's AI AOI machine for PCB is an alternative to dedicated AOI cameras. It builds the whole inspection machine in Batam and puts its AI on any brand of high-resolution camera, so you are not locked to one camera vendor. Accuracy on PCBs is ≥95%.

How does AI inspect both sides of a PCB in one cycle?

INDUSIA's machine checks side A, then a mechanical holder flips the board under the cameras and the AI checks side B in the same cycle. There is no robot arm. Good and defect boards then go to separate bins.

Can it replace an existing AOI machine like Keyence, OMRON, or Cognex?

As a system, yes — INDUSIA is built as an off-the-shelf-AOI alternative with ≥95% detection accuracy and a local support team in Batam. Note the vendor camera itself can't be reused: it is locked to its own controller and proprietary port — INDUSIA pairs its AI with any standard high-resolution camera instead.

We already have an SMT inspection machine. Do we need to replace it?

No. Our AI re-checks the boards your SMT machine flags and clears the obvious false calls. Only real doubts go to the operator. No new cameras and no machine changes.

Can our operators teach the AI a new defect?

Yes. In the Visual Editor they mark good and defect regions on the PCB image, train, test and send the model to the machine. No data scientist is needed.

Updated

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