RegisterCatalyst Project
Manufacturing Predictive Maintenance using 5G
Failures of manufacturing equipment cause enormous costs directly through damage to expensive machines, and indirectly through lost production and missed deadlines. Traditional scheduled maintenance is inefficient as functioning machines are halted and maintained ‘just in case’.
Data-driven approaches allow reduced downtime by servicing machines only when they actually need intervention. Sophisticated machine learning algorithms process vast amounts of data from multiple sensors, and learn to spot subtle clues that equipment is likely to fail. Such Predictive Maintenance has great benefits, reducing planned maintenance costs, whilst minimising costs due to unexpected failures.
This Catalyst will explore how 5G technology in a challenging factory environment allows massive volumes of sensor data to be collected reliably and quickly, enabling machine intelligence Predictive Maintenance algorithms running in edge Cloud to spot incipient problems and respond pre-emptively in milliseconds.
Innovative business models allowing value-add solutions such as Predictive Maintenance to be brought to market effectively will be explored. This Catalyst will explore how business federation and platform models can be used by the telecoms industry to offer such vertical solutions to a global market.
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Manufacturing Predictive Maintenance using 5G