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AI Autopilot — 25日間の管理されたパイロットで+6%のスループットと年間$781Kの利益増を達成。Brasil Mineral #441(2024年7月)。パイロット結果を見る
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実体経済を動かすAI。鉱業。産業。音声。2019年よりブートストラップ運営。
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プライバシーポリシー利用条件
Industrial · Welding & Joining

Welding — AI-assisted robotic MIG/TIG/laser

Vision-in-the-loop welding. AI monitors arc signature, bead geometry, and seam tracking to adjust wire-feed, current, travel speed, and torch angle in real time — dropping defect rates and reducing rework.

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ライブデモを試す
Robotic MIG welding arm with bright arc and sparks

概要

Robotic welding is deterministic on paper and chaotic in reality. Part fit-up varies by tenths of millimeters, wire spool diameter shifts as it empties, shielding-gas pressure drifts, and tacks move slightly between jigs. Every one of those factors changes the weld — and most welding cells still run on static recipes.

Inspection catches defects after they are sunk cost. A single porosity stretch on a high-value structural weld can mean hours of grinding, re-welding, and X-ray re-qualification. AI Autopilot shifts defense from inspection to prevention.

BrainiAll AI reads high-frame-rate arc imagery, seam laser profilometry, and arc-signature spectra. It corrects parameters in real time to keep the weld inside the sound-weld envelope — and logs every deviation with explainability for QA audits.

-30-60%Weld defect rate reduction
↓Rework hours per shift
↑First-pass yield
ISO 3834Audit-ready weld log

Autopilotの機能

連続的・多変数制御 — 単一ループPIDではありません。アドバイザリ層アーキテクチャにより安全性はそのまま維持されます。

Live arc-signature analysis

Classifies spray / globular / short-circuit transfer at high frequency and flags out-of-envelope conditions.

Seam tracking

Laser profilometry guides torch path correction within microns of the joint centerline.

Adaptive parameter correction

Adjusts wire-feed, voltage, travel, and torch angle in-cycle as conditions drift.

Defect prediction

Flags porosity, lack-of-fusion and undercut risk from signature before inspection confirms.

Full traceability

Every bead logged with parameters, imagery, and classifier output — audit-ready under ISO 3834 / AWS D1.1.

継続的に調整される変数

AIはサークルのすべてのセンサーを読み、最適なセットポイント組み合わせをリアルタイムで解決します。

  • Wire feed speed (WFS)Direct driver of deposition.
  • Arc voltage & currentDetermines transfer mode.
  • Travel speedBead width and penetration.
  • Torch angle & CTWDGeometry-sensitive; AI adjusts during curved paths.
  • Shielding gas composition / flowCritical for arc stability.
ビジネスケース

For a structural fabrication line doing 20,000 linear meters of welding per month, dropping defect rate from 2% to 0.7% directly eliminates roughly 260 meters of rework per month — a full shift of labor recovered every week.

既存のコントロールシステムと統合

FroniusLincoln ElectricESABKUKAABB RoboticsFANUCYaskawa

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