Review
Review DPF · Using AI to avoid downtime in intralogistics
September 07, 2021
Challenge:
The aim of the challenge owner was to implement predictive maintenance for the transport vehicles, which would enable failure prediction. By recognising patterns in the existing alarm system and installing additional sensors, a health status is to be mapped for each vehicle.
Solution:
Acoustic signals from the OHVs are recorded using a data collection kit. The classification of the OHVs is based on the acoustic anomalies recognised in this way, a ‘criticality metric’ of faults from the existing MACs database and the recognition of similar fault patterns in failed vehicles. The MVP developed enables unplanned downtimes to be avoided and optimised maintenance to be carried out with the help of a user-friendly dashboard.
Challenge owner: GlobalFoundries
Project partners: Telekom MMS
HansKlingstedt
Senior Project Manager
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