headquartered in Malaysia, Petroliam Nasional Berhad (PETRONAS) is a multinational oil and gas ompany that produces 2.4 million barrels of oil equivalent per day. The organisation aims to achieve net-zero carbon emissions by 2050 but to help it move closer to attaining this sustainability goal, it needed to find a way to optimise the performance of its plant equipment to make it more reliable and stable.
Like any industrial organisation that operates machinery, PETRONAS must ensure its equipment runs moothly at all times to be able to serve customers. Although PETRONAS was able to schedule aintenance activities in advance, it faced unexpected critical rotary equipment failures that can result in unplanned downtime, potentially shutting down an entire plant and leading to catastrophic consequences.
PETRONAS’s plants were at risk of critical equipment failure because the engineering division did not have access to the right information to gain advance warning of problems. Keen to optimise the performance of equipment to improve plant reliability and reduce the risk of downtime, the engineering division wanted to implement an asset performance management (APM) solution. This would give plant operators an insight into impending equipment failures and empower them to proactively fix the equipment before bigger problems ensued.
Consequently, PETRONAS opted for AVEVA Predictive Analytics, an APM solution that provides early warnings and diagnoses of issues with 151MANUFACTURING & RESOURCES equipment days, weeks or even months before it fails. This helps asset-intensive organisations such as PETRONAS to reduce equipment downtime, increase reliability, improve performance and safety, and decrease operational and maintenance expenditure.
“The key outcome was successfully achieved. We had data transparency across the businesses to improve business agility and decision making. This visibility is transforming the way we are working in PETRONAS.”
Abdul Rahim Norman, Staff Engineer – Process Simulation and Optimization, PETRONAS
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