Manufacturing · Robotics
From managing robots to optimising an intelligent fleet.
A manufacturer running AMRs and AGVs had limited visibility into route congestion, charging downtime, idle fleet utilisation and cross-zone movement inefficiencies.
Wyzwanie
Z czym mieli do czynienia.
Route congestion
Robotic traffic created congestion hotspots across zones.
Idle & charging downtime
Fleet utilisation and charging were unmanaged.
No fleet-level view
Robots were managed as individual machines, not a fleet.
Nasze podejście
Vendor- neutralny, wyprowadzony - led.
UWB for real-time robotic positioning, BLE for asset-interaction tracking, AGV/AMR telemetry for route analytics, and AI orchestration for congestion, idle-time and predictive movement optimisation.
Jak to rozwiązaliśmy?
To, co dostarczyliśmy.
- UWB RTLS real-time robotic positioning
- BLE asset-interaction tracking
- AGV/AMR telemetry route analytics
- AI fleet orchestration — congestion, idle, predictive optimisation
Wyniki
Wynik, który widział zarząd.
Higher
AMR/AGV utilisation
Niższe
idle charging time
Bezpieczniejszy
robotic traffic
Higher
throughput
“We stopped managing robots as individual machines and started optimising them as an intelligent fleet.”
— Director of operations, industrial manufacturing (client anonymised)
Stosowana technologia
Stos za nim
UWBBLEAGV/AMR telemetryAI orchestration