The goals are to support process optimization and preventative maintenance, reduce operational downtime, and improve and limit the need for manual inspections.
It uses AI models and deep learning algorithms to predict maintenance needs and monitor the performance of equipment performance by interpreting data received from equipment-mounted sensors, including pressure, temperature and vibration.
The deployment will now be extended to all ADNOC facilities across thousands of critical production items, including compressors, valves and generators.
Results from the pilot phase of Neuron 5 suggest the technology could cut the number of unplanned shutdowns by 50% and improve by 20% planned maintenance intervals across operations. This can release ADNOC operators to focus on more productive activities.
