Případová studie · AerospaceAnonymizované na žádost. Pojmenované odkazy pod NDA.
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.

Manufacturing · RoboticsAMR / AGV fleet intelligenceHybrid RTLS / RFID + analytics · measured outcomes.live asset positionHigherAMR/AGV utilisationNižšíidle charging time
Výzva

Proti čemu stáli.

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.

Náš přístup

Vendor- neutrální, mimo provoz.

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 jsme to vyřešili.

Co jsme doručili.

  • UWB RTLS real-time robotic positioning
  • BLE asset-interaction tracking
  • AGV/AMR telemetry route analytics
  • AI fleet orchestration — congestion, idle, predictive optimisation
Výsledky

Výsledek, který rada viděla.

Higher
AMR/AGV utilisation
Nižší
idle charging time
Bezpečnější
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)

Použitá technologie

Ta hromádka za ní.

UWBBLEAGV/AMR telemetryAI orchestration
Mohl by to být váš program?

Řekni nám, kde jsi uvízl.

30 minut na vašem případu použití, čísla, a co by skutečně přesunout váš KPIs. Vendor- neutrální, žádná plošina.

Promluvte si s poradcem.