FEATURE : STORAGE actual failure has reduced unscheduled downtime and saved PETRONAS millions of dollars .
Many of the catches helped to reduce critical rotating equipment failure and downtime and have led to improved reliability through proactive asset monitoring and maintenance . For example , an instrumentation fault was identified leading to a catch in a liquid separator that saved PETRONAS US $ 222K ( RM934K ) in potential asset failure and wasted material .
A potential motor failure was also caught when AVEVA Predictive Analytics identified increases in the motors lube oil temperature , the winding temperature and the hot air temperature , saving US $ 82K ( RM344K ) in equipment replacement .
In another situation , a mechanical fault was identified allowing maintenance engineers to pinpoint a water supply temperature out of specification along with an increase in bearing temperature . Catching this issue before it cascaded into a major equipment failure saved Petronas US $ 48K ( RM 202K ).
Reduced maintenance costs , a safer plant , and improved equipment utilization
Part of value creation at PETRONAS comes from cutting maintenance costs . Using the AVEVA APM solution on their Azure cloud platform enabled the team to streamline day-to-day operations and regular maintenance cycles . They can analyze the problems in detail and take further proactive action to reduce the chance of reoccurrence , which further contributes to reduced maintenance costs . Avoidance of equipment failures and unplanned shutdowns has also contributed to better safety records and a safer working environment .
Improved asset utilization and faster decision-making drive efficiencies
AVEVA Predictive Analytics uses AI to highlight the slightest deviation from normal operational profiles . Through detailed analysis , the team has been able to identify underperforming assets and take remedial action to improve equipment efficiency . actions each time anomalies are triggered . This eliminates the need for manual time-consuming investigations and decisions can be made quickly , which in turn , boosts productivity .”
What ’ s next for PETRONAS ?
Following the successful pilot across four plants , PETRONAS has deployed AVEVA Predictive Analytics at an additional 10 plants with a total of 150 equipment trains . PETRONAS aims to continue rolling out the APM solution in the cloud to all its assets to enjoy similar results across the business . PETRONAS also uses cloud-based AVEVA Unified Supply Chain to optimize its entire supply and distribution network , cutting crude evaluation time and reducing margins .
Azlan Ayub , P-MMPD Lead , PETRONAS , said : “ The PETRONAS Machinery Monitoring and Prescriptive Diagnostics system – based on AVEVA ’ s advanced analytic tools that utilize Machine Learning and Artificial Intelligence – will be scaled up across our business . We therefore expect the value delivered to PETRONAS from our AVEVA solution to increase accordingly , as we continue to collaborate with our technology partners to support our Moving Forward Together strategy .”
Boris Marrone , Vice President , Asia Pacific and Head of South Asia and South East Asia , AVEVA , said : “ Predictive analytics make organizations more efficient and resilient by transforming them from being reactive to being proactive . Organizations can implement asset strategies designed to avoid unplanned downtime for their most critical assets , and also work out corrective or preventative strategies for the less vital equipment .
“ This , in turn , allows industrial organizations to better optimize capital and operational expenditures , while realizing financial savings by avoiding productivity losses or wasted man hours . Predictive analytics empowers industrial organizations to be more proactive in their work .” p
Salim Sumormo , Custodian ( Rotating Equipment ), PETRONAS
Azizol Kamaruddin , Principal ( Rotating Equipment ), PETRONAS , said : “ Not only does our AVEVA solution deliver early detection of anomalies and failure , it also enables us to institutionalize our years of machine operation experience into a digital platform . We ’ ve integrated the PETRONAS failure mode and effects analysis ( FMEA ) methodology into AVEVA Predictive Analytics , and the solution prescribes the corrective
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