Eliminate Unplanned Downtime with Predictive Augmented Intelligence
How a leading Gas Distribution Network utilized AI-driven anomaly detection to prevent critical valve failures and slash Non-Productive Time (NPT).
Business Objective
The client needed a highly reliable valve and pump health monitoring system. The primary goals were to enhance predictive maintenance capabilities, build a valve and pump health monitoring system to reduce unplanned downtime, cut operating costs, and decrease Non-Productive Time (NPT).
They faced three critical hurdles:
Unanticipated Downtime
Critical shop-floor assets (valves, pumps) failing without warning, disrupting the entire production line.
High Operational Expenses (OPEX)
Reactive maintenance and static servicing schedules were inefficient and expensive.
Safety Risks
In environments handling gas or hazardous materials, undetected equipment degradation can lead to dangerous leaks.
The AI Solution
We deployed a dual-layered AI anomaly detection framework that ingests real-time IoT and sensor data (such as hydraulic pressure and flow rates) to monitor equipment health.
Instead of relying on generic thresholds, the system uses a combination of supervised machine learning (to classify known healthy vs. degraded states) and unsupervised learning (to instantly detect abrupt, zero-day behavioral shifts).
This allows the AI to automatically translate live sensor data into early-warning alerts, equipping operators with automated decision support.
Supervised Machine Learning
Distinguished healthy vs. degraded valve actuators using hydraulic pressure and flow sensor data recorded during opening and closing events.
Unsupervised Anomaly Detection
Detected abrupt behavioural changes by comparing sensor readings across consecutive operational events – catching anomalies no baseline could define in advance.
Business Impact & Value Delivered
The Augmented Intelligence models successfully shifted the client’s operations from reactive to proactive, delivering immediate, measurable ROI.
Productivity Increase
Shifted scheduled maintenance from a fixed quarterly cycle to targeted interventions once every six months.
Drop in Asset Failures
Enabled maintenance teams to intervene with high confidence long before physical breakdowns occurred.
Continuous Monitoring
Achieved full visibility of valve integrity, directly mitigating the risk of hazardous environmental leaks.
Reduced Equipment Downtime: Significantly lowered Non-Productive Time (NPT).
Optimized OPEX: Streamlined maintenance schedules by servicing machines only when the AI indicated a high probability of failure.
Improved Safety: Eliminated the risk of hazardous leaks by ensuring constant, real-time valve integrity.