Technology Record - Issue 22: Autumn 2021

153 closely monitor operations, spot anomalies and generate early warnings. Through detailed anal- ysis, the team has been able to identify under- performing assets and take remedial action to improve equipment efficiency. PETRONAS’s use of AVEVA Predictive Analytics has also improved collaboration between the plant operators and specialists at the PETRONAS Centre of Excellence, which acts as a centralised remote monitoring centre. The business units can constantly share updates and feedback related to the detected faults and when the operators spot deviations from normal operations, the subject matter experts at COE can quickly recommend corrective action via the case management feature. They can analyse problems in detail and take fur- ther proactive action to minimise the chance of reoccurrence, which has also contributed to reduced maintenance costs. “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,” says Azizol Kamaruddin, principal for rotating equipment at PETRONAS. “We’ve integrated the PETRONAS failure mode and effects analysis methodology into AVEVA Predictive Analytics, and the solution prescribes the corrective actions each time anomalies are triggered. This eliminates the need for manual time-consuming investiga- tions and decisions can be made quickly, which in turn, boosts productivity.” Following a 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 Microsoft Azure cloud to all its assets and enjoy similar results across the business. The organ- isation also uses cloud-based AVEVA Unified Supply Chain to optimise its entire supply and distribution network, cutting crude evaluation time and lowering margins. “The PETRONAS Machinery Monitoring and Prescriptive Diagnostics (P-MMPD) system – based on AVEVA’s advanced analytic tools that utilisemachine learning andAI –will be scaled up across our business,” says Azlan Ayub, P-MMPD lead at PETRONAS. “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 sup- port our ‘Moving Forward Together’ strategy.” MANU FAC TUR I NG & R E SOUR C E S