Technology Record - Issue 22: Autumn 2021

152 www. t e c h n o l o g y r e c o r d . c om P ROF I L ED : P E T RONA S or failures, and to enable the teams to undertake improvements as needed. Data collected by the sensors in the instru- ments and equipment pinpoints the tiniest devi- ations from what PETRONAS has trained the software to consider as ‘known good behaviour’. This is more effective than setting high and low thresholds that trigger an alarm when reached, because by then, operations have already spun out of control. PETRONAS’s AVEVA Predictive Analytics solution spots the problem as it grows away from ‘known good behaviour’ and before it leads to a catastrophic failure. The streamlined data integration between AVEVA’s APM solution on Microsoft Azure and the PI System was a significant success factor in the project. “We’ve been using PI System as our standardised data historian platform for many years,” explains Salim Sumormo, custodian of rotating equipment at PETRONAS. “We were looking to add further value to the data gath- ered to optimise plant operations throughout our business. We chose cloud-based AVEVA Predictive Analytics not only because of its ability to accurately predict equipment failures in advance, but also because it easily integrates with PI System and because of its intuitive look and feel which helped our teams get up to speed quickly.” AVEVA’s solution also works in parallel with PETRONAS’s existing traditional plant control (DCS) system. Operation engineers use the DCS system to operate the plant, while maintenance and reliability engineers use AVEVA Predictive Analytics for their daily tasks and monitor assets across the sites. Everyone in the team has visibility of the systems – from technicians to plant managers and management teams. With these capabilities in the cloud, PETRONAS can remove silos and build new and more collabora- tive ways of working. In the first year of pilot implementation (2020) with 200 models deployed, AVEVA’s solution accurately identified 51 major early warnings of impending equipment failures, including 12 high-impact warnings. PETRONAS’s team was able to resolve these issues ahead of actual failure, significantly decreasing unscheduled downtime and saving the organisation a total of US$17.4 million. This also generated 14 times ROI. Many of these warnings helped to reduce crit- ical rotating equipment failure and downtime, indicating that proactive asset monitoring and maintenance leads to improved plant reliability. For example, an instrumentation fault was iden- tified leading to a catch in a liquid separator that saved PETRONAS $222,000 in potential asset failure and wasted material. AVEVA Predictive Analytics also saved $82,000 in equipment replacement costs by detecting potential motor failure via increases in the temperature of the hot air, winding and lube oil in the motor. In another situation, the solution found a mechanical fault, allowing maintenance engineers to pinpoint and resolve issues with the temperatures of a water supply and a bearing. Catching this issue before it turned into a major equipment failure saved PETRONAS $48,000. Another benefit is that using AVEVA’s APM solution on its Microsoft Azure cloud platform has enabled PETRONAS to streamline day-to-day operations and regular maintenance cycles. The decrease in equipment failures and unplanned shutdowns has also contributed to a safer working environment and better safety reports. AVEVAPredictiveAnalytics has improved asset utilisation and enabled faster decision-making too. It uses artificial intelligence (AI) to high- light the slightest deviation from normal opera- tional profiles, enabling the PETRONAS team to “Not only does our AVEVA solution deliver early detection of anomalies and failure, but it also enables us to institutionalise our years of machine operation experience into a digital platform” A Z I ZOL KAMARUDD I N , P E T RONA S