Operational Disruption Management

AI helps operations teams detect disruptions, reuse knowledge from similar cases, and reduce downtime or manual recovery work.

Business impact

• Downtime — SLNG says it aims to reduce downtime with predictive technology and avoid disruptions at the LNG terminal.
• Maintenance costs — SLNG says it aims to reduce maintenance costs through predictive use of data.
• Asset availability — SLNG says it uses predictive technology and sensor data to maximise asset availability.

Data requirements

• Historical process disruption information (tabular) — Airbus uses information about similar problems from other shifts or processes.
• Sensor data (sensor) — SLNG uses usage patterns collected by sensors to detect potential failures.
• Operational and business data (tabular) — SLNG integrates data across finance, HR, procurement, and maintenance.

AI methods and techniques

• Predictive analytics — SLNG uses predictive technology and sensor data to detect potential failures before they cause disruption.
• Pattern matching — Airbus uses information about similar problems from other shifts or processes to suggest solutions.
• Automation — SLNG uses automation to reduce manual work around operational processes and workflows.

Industries

Real-world evidence

2 documented case studies on record.

Companies using this: Airbus, Singapore LNG Corp. (SLNG).