AI Predictive Maintenance in Oil and Gas Industry: Nanoprecise Saves $130,000 and 4 Hours of Downtime for Industry Leader
Summary
Nanoprecise partnered with one of the largest Oil and Gas companies in Vietnam—responsible for gathering, manufacturing, storing, and distributing massive volumes of gas products.
By deploying MachineDoctor™, a wireless sensor that measures six key parameters—including vibration monitoring suitable for oil and gas applications— as part of Nanoprecise’s AI-driven predictive maintenance solution, the company gained visibility into critical asset performance across its operations.
The system detected a Stage 3 unbalance fault on a key blower motor, enabling maintenance teams to intervene before failure.
The result: Over $130,000 in downtime costs avoided, 4 hours of unplanned downtime saved, and a major shift from reactive to proactive, ai-driven predictive maintenance solutions for oil and gas equipment.
Oil and Gas Customer Profile
This leading Vietnamese Oil & Gas enterprise oversees an extensive network of production and processing facilities. Its operations depend heavily on the continuous performance of rotating equipment such as blowers, motors, compressors, and pumps.
Because personnel were restricted from approaching the equipment while it was running, manual inspections were limited, and early fault detection was nearly impossible—making predictive maintenance in the oil and gas industry essential to improve reliability and safety.
The Challenge
The boiler fan motors operate under variable loads and speeds. Without continuous monitoring, subtle faults such as imbalance or misalignment can go unnoticed until they escalate in unmonitored machines located in remote or hazardous areas made maintenance both inefficient and risky.
Without condition data, maintenance was reactive—leading to costly unplanned shutdowns and increased safety hazards for field technicians.
Oil and Gas Predictive Maintenance Solution Deployed
To address these challenges, the plant deployed Nanoprecise’s AI-driven maintenance solution, including the wireless MachineDoctor™ sensor, which measures six variables, including vibration, on all critical oil and gas equipment. This implementation formed the foundation of the oil and gas plant’s predictive maintenance program.
The solution included:
- Wireless sensors with 6-parameter machine condition monitoring (including vibration and acoustic monitoring)
- Fault identification and condition-based maintenance alerts
- Automated AI fault notifications using alarm thresholds
- Cloud-based dashboard for visibility and predictive analytics (view dashboard walkthrough video)
The system quickly detected a significant vibration anomaly on Blower H-1741 Motor DE, triggering a Stage 3 unbalance fault alarm and prompting immediate corrective action.
Observation & Analysis
Fault Detected: Blower H-1741 Motor Drive End (DE)
Fault Mode: Unbalance
Severity: Stage 3 Alarm – Requires Immediate Attention
Observations:
- Vibrations were steadily increasing in all three directions.
- FFT analysis and trend data confirmed unbalance symptoms.
Recommendations:
- Rebalance the system and re-torque all base bolts.
- Clean the impeller to remove debris buildup.
- Inspect and replace Motor DE/NDE side bearings if deteriorated.
By leveraging the AI-driven predictive maintenance insights, the maintenance team took early corrective actions—preventing performance degradation and costly downtime.
Outcomes & Impact
Avoided Downtime Costs: $130,000+ in potential production losses prevented.
Early Fault Detection: Identified faults before failure, saving over 4 hours of downtime.
Enhanced Safety: Reduced manual inspections in hazardous areas
Operational Efficiency: Transitioned from reactive to predictive, data-driven maintenance.
Equipment Reliability: Continuous monitoring ensures long-term asset performance
Conclusion
Nanoprecise helped this major Vietnamese operator transition from reactive to predictive maintenance by deploying AI-driven solutions for their oil and gas equipment, boosting reliability, safety, and uptime across all critical systems.
By identifying unbalance faults early with MachineDoctor™ wireless sensors, the company avoided expensive production losses and gained continuous, intelligent insights into machine health. Want to see it work for you?
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