Industrial AI in automotive wheel plants
An automotive wheel plant is one of the most demanding operations in manufacturing: disc stamping, rim profiling and flash butt welding, 360° weld assembly, e-coat and paint, and a battery of fatigue and impact tests that qualify every part number. All of it against a sequenced OEM schedule, with no inventory buffer, and with traceability that must reach back to the steel heat of every single wheel.
The problem is not a lack of technology. These plants already run statistical process control, sensors and mature business systems. The problem is everything analogue that surrounds those systems and is lost today: the first-piece sheet that takes a full shift to be digitised, the flash butt welder panel that overwrites its parameters every cycle, the supplier email read once there is no margin left, the laboratory spreadsheet somebody types in a second time, the coil delivery note transcribed with a truck waiting.
This page collects twelve IRIS use cases applied to this sub-sector, grouped by building block: Connect to capture what is lost today, Edge so that machine vision controls the line at cadence, and Agents so that evidence organises itself. Each case sets out the concrete problem, how the architecture fits, the measurable before and after, and a conservative return range.
Capture without changing habits: photo, voice, email, integrations
Paperless press setup
Payback 4-9 months · from 4-8 h of latency to second zero
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The welder panel speaks
Payback 5-10 months · defers capex above 500 K€
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The alert that skips EDI
Payback 4-8 months · from next day to minutes
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Hands-free maintenance rounds
Payback 3-8 months · the fastest: no plant hardware
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First piece approved in two taps
Payback 4-9 months · a signature with evidence attached
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The lab spreadsheet reaches the ERP
Payback 4-8 months · from 4-6 quality licences to 1
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Coil receiving without typing
Payback 3-7 months · from 30-45 min per truck to two
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The marker reads from the MES
Payback 4-9 months · from two keystrokes per changeover to zero
See the case →Machine vision on the line, in real time
More cases in automotive
- Digital andon with automatic escalation — the light tower comes on, but if the line lead is at the far end of the shop floor, the stop gets longer.The andon lights up; iLEAN escalates the alert only if nobody responds and logs the response time at…
- Digital 5S on the assembly line — the standard drifts between audits; finding out on the next monthly walk is too late.iLEAN sustains 5S between audits: gemba walk with photo and voice, verification of the workstation…
- Instrument cluster control with AI — the end-of-line test samples seconds; the fine cosmetic defect reaches the OEM.iLEAN verifies 100% of the cluster display sequence — pixels, brightness, icons, clips — and matches the…
- The die changeover validated before the first strokeEdge checks that the mounted die is the one the active order requires before the first stroke: no more…
- The process engineer dictates at the press, and the PFMEA stays aliveThe process engineer dictates what they see at the press without stopping, and the living PFMEA is fed…
- OEM program setup validated by Edge vision before startupEdge cameras validate mold, LED reel and fixture before the next OEM program starts; AI Jidoka locks the…
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