Industrial AI in automotive wire harness plants
This hub groups the IRIS use cases landed on automotive wire harness manufacturing: cutting and crimping, ultrasonic splices, manual assembly on boards, 100% electrical test and sequenced shipment to OEM assembly plants.
It is a sub-sector defined by one particular trait: the process IS the labour. Most of the transformed cost is people assembling by hand, and turnover and absenteeism are structural, so part of the workforce is always on the learning curve. Quality is not decided at a machine: it is decided by whether someone with a few weeks in the role executes dozens of operations correctly, shift after shift.
You will find twelve cases organised in three blocks —Connect, Edge and Agents— running from shop-floor paper to the flagship against the customer line stop. Each with its real problem, its fit with IRIS, its measurable before and after, and a conservative return range.
Capture without changing habits: photo, voice, email, integrations
The traveler sheet, with nothing lost on paper
Payback 4-9 months · from 4-8 h of latency to second zero
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The legacy crimp press starts talking
Payback 5-10 months · crimp drift scrap down 30%
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The customer alert that is not missed
Payback 3-8 months · from hours of latency to minutes
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The supervisor walks and talks to the system
Payback 4-9 months · weak signals recorded continuously
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Nothing enters the system unsigned
Payback 3-7 months · less containment over-scope
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The crimp lab sheet reaches the ERP on its own
Payback 3-6 months · from 6 to 1 quality licence
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Reel receiving, in two photos
Payback 4-8 months · from 4 to 1 receiving licence
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The test bench stops being an island
Payback 4-8 months · claims answered in minutes
See the case →Machine vision on the line, in real time
Agents that plan, document and coordinate
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