Page 12 - Industrial Technology EXTRA - 15th June 2020

saving potential in maintenance costs. To improve AI is certainly playing a key role in
these strategies further, edge computing technology manufacturing, moving from vision recognition to
[as described earlier] is being used to leverage the skill learning and predictive maintenance for failure
value of manufacturer’s data using advanced prevention, however it has further scope for
analytic algorithms executed on the Edge of the providing operational benefits and efficiencies.
shop floor. When detecting impending faults and informing
Another important category of process data is operators how to fix problems for example we see AI
the one that is used for traceability and consumer again coming to the fore.
information, especially in the food sector. This can AI is being used to increase the effectiveness of
be employed, for example, to prove compliance predictive maintenance for plant automation assets.
with the cold chain or to attach origin information to Cloud-based solutions using AI platforms analyse
food packaging that can be called up via a QR code. operational data and can optimise maintenance
Data collected from PLCs, controls and drives regimes based on actual usage and wear
centrally and processed locally using edge characteristics. Predictive maintenance for plant
computing reduces the bill for storage space in the automation assets can of course reduce operational
cloud in addition to delivering many other costs, increase asset productivity and improve
advantages for faster production control and process efficiency.
monitoring. gb3a.mitsubishielectric.com

June 2020 • INDUSTRIAL TECHNOLOGY EXTRA! • p12