SUCCESS STORY / CONNECTED MES FOR OPTICAL CONNECTIVITY
From paper records to unit-level traceability
An optical connectivity manufacturer builds fibre, cable and connector components by hand, with no ERP and paper records at every step. Thingple is replacing the paper with a connected MES: a screen at every station, a clip-on RFID tag that follows each unit, and AI vision in place of the microscope.
Under way: the first version goes live in mid-November 2026, with full operation planned by the end of December.
- Customer
- Optical connectivity manufacturer
- Industry
- Optical components
- Location
- China
- Solution
- Manufacturing excellence · Connected MES
- Status
- Under way
THE SCOPE
A precise product, many steps
The first phase covers every existing production and inspection step on the pilot lines.
THE CHALLENGE
Paper records and eyes on a microscope
The line is labour-intensive and the product is small and valuable. Without an ERP or MES, nobody can see output or yield as it happens, and one unit cannot be traced.
Paper everywhere
Work instructions, job records and logbooks are on paper. Changing a line means swapping printed sheets by hand, and versions slip.
Judged by eye
Fibre end faces are checked by eye under a 400× microscope. It is slow, and one inspector's call can differ from another's.
Hard to trace
Products carry no unique code, so a customer complaint cannot be traced back to the steps one unit went through.
HOW IT WORKS
Screen, clip and camera at every station
Three simple parts carry the system. Line staff see one clear screen, and the checks happen behind it.
Station screen
Each station has an industrial display showing the digital work instruction and the job. Move the screen and the station moves with it, so lines can be reorganised without rewiring.
Hardware and MESClip-on RFID
A passive RFID clip fastens to each unit without damaging it, is read at each station to check the step, and is removed and reused before packing.
RFIDAI vision
Industrial cameras with a deep-learning model take over end-face and appearance checks, and keep a growing library of quality images.
Thingple AIAt every station: read the RFID clip, check the unit is in the right state, show the work instruction, do the work, then report. If a unit arrives at the wrong step, the system stops it.
AI INSPECTION
Learns from the customer's own engineers
The model starts cautious and improves as samples build up.
Cautious start
The model leans towards false alarms rather than missed defects, then relaxes as samples grow.
Goal: 90%+
The aim is above 90% accuracy within about a month of go-live, with a few results checked by people.
Their engineers in control
Customer engineers can correct a result directly, and each correction retrains the model without a call to the supplier.
BUILT IN BLOCKS
Start with production. Add the rest when ready.
The system is modular. Later phases can be combined or run in parallel, without rebuilding the base.
Phase 1
Core production
Station screens, RFID unit traceability, AI inspection of key steps, step-by-step error-proofing, staff KPIs and a basic dashboard.
Phase 2
Management
Warehouse, scheduling and quality modules, links to ERP and purchasing, and a plant data platform.
Phase 3
Intelligence
Industrial AI models, predictive quality and maintenance, early risk warning and a digital twin.
THE PLAN
Pilot first, then copy
Everything is tested on two existing lines, so the new plant can reuse a proven design. At full scale it is meant to manage 300 to 500 work positions.
First version live
Screens, work instructions, job orders and a basic dashboard, ready to show.
Mid-Nov 2026Full operation
Unit-level RFID traceability, AI inspection, error-proofing and equipment links.
End-Dec 2026Copy to the new plant
The proven design is repeated across the new factory's lines.
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EXPLORE YOUR OPERATION
Where could better
data help your plant?
Tell us about your warehouse, your lines or your quality challenges.
Email info@thingple.com ↗