Case Study
25% reduced downtime with KPI-driven performance monitoring of flares to identify anomalies and reduce pollution
- Industry: Energy (Oil & Gas, Renewables) ​​
This multinational oil and gas company is among the world’s largest companies out of any industry. This $381 billion company has over 86,000 employees worldwide and a presence in more than 70 countries.
Challenge
- Unpredictable downtime: frequent service interruptions due to pipeline corrosion and leakage
- Risk exposure: high risk of environmental and operational hazards
- Lack of visibility: inadequate real-time monitoring of asset health
Solution
Aligned Automation implemented a data-driven approach using IoT sensors and AI/ML models to predict pipeline corrosion, leakage, and overall asset health. This enabled:
- Predictive maintenance: AI/ML models provided early warnings for pipeline issues
- Efficient workflow: closed-loop, streamlined processes for quick action
- Continuous monitoring: real-time visibility into asset health across thousands of miles of pipeline
Capabilities leveraged
Data & Analytics
Process Transformation
AI & ML
Outcome
25%
Reduced downtime:
significant reduction in service interruptions
Risk mitigation:
lowered operational and environmental risks
Asset health monitoring
enabled continuous visibility into asset health
Cost efficiency:
users engaged across 37 offshore drilling units in 10 countries