Predictive Maintenance for Asset Reliability

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Reduce unplanned downtime and maintenance spend with GB18’s AI‑driven predictive maintenance solutions. Proven in high‑stakes oil & gas operations, our models forecast failures before they occur, protecting safety, production targets and bottom‑line performance across any asset‑intensive industry.

From Reactive Repairs to Data‑Driven Uptime

Unexpected equipment failures cost the global energy sector billions in lost production, environmental penalties and safety incidents. GB18’s PhD‑led reliability team first tackled these challenges on offshore platforms and LNG facilities—remote sites where a single compressor outage can halt an entire value chain.

We ingest high‑frequency sensor streams, historian logs and maintenance records, then combine anomaly detection, survival analysis and physics‑informed models to forecast degradation days or even weeks in advance.

Common Pitfalls We Eliminate

Siloed Data

Disparate OT and IT repositories hide causal patterns. We unify sources in real time, preserving lineage so root‑cause signals remain intact.

Over‑Fitted Models

Algorithms trained only on common events overlook rare, catastrophic failures. Our ensemble approach balances precision and recall, retaining sensitivity to low‑frequency—but high‑impact—anomalies.

Alert Overload

Generic thresholds spam technicians with noise. GB18 embeds context‑aware prioritisation and prescriptive guidance, turning raw alerts into clear work orders that schedule parts, personnel and optimal shutdown windows automatically.

The Outcome

Fewer unplanned shutdowns, optimised spares inventory and a culture of proactive reliability that translates seamlessly from oil & gas to manufacturing, utilities, transportation and beyond.

GB18’s End‑to‑End Predictive Maintenance Framework

Effective predictive maintenance is a multidisciplinary effort—data engineering, advanced analytics and domain expertise must work in unison. GB18 delivers via agile sprints, ensuring stakeholders see measurable value early while keeping risk and budget under control.

Data Fusion & Quality Assurance

We integrate SCADA, MES, ERP and condition‑monitoring feeds, cleansing and aligning them with time‑series reconciliation and sensor drift correction. Robust data lineage and validation checks guarantee the models learn from trustworthy inputs, not noisy anomalies.

Model Development & Validation

Physically‑constrained machine‑learning ensembles combine vibration signatures, thermodynamic curves and historical failure modes. K‑fold cross‑validation on imbalanced datasets, plus synthetic minority oversampling, ensure rare failure patterns remain detectable without inflating false positives.

Alert Orchestration & Workflow Automation

Predictions trigger CMMS work orders, spare‑parts procurement and technician scheduling via API integrations. Priority scoring considers asset criticality, EHS risk and production impact, ensuring maintenance crews tackle the most business‑critical tasks first.

Transferring Energy‑Sector Expertise to Other Industries

The harsh conditions of oil & gas taught us to build resilient systems that tolerate noisy sensors, variable loads and strict safety standards. Those same principles now drive success in diverse sectors.

Manufacturing Optimisation

We apply multivariate anomaly detection on CNC machines and assembly lines, catching bearing wear and tool misalignment early, reducing scrap rates and extending machine life without costly over‑maintenance.

Rail & Transportation Reliability

Integrating onboard diagnostics with trackside IoT sensors, our models forecast wheel‑flat formation, overheating axles and signalling faults, improving passenger safety and network punctuality.

Utility Grid Stability

Real‑time analytics on transformer temperatures, load profiles and weather data predict failures days in advance, allowing grid operators to reroute power and schedule repairs without service interruptions.

Sustaining Long‑Term Reliability Gains

Predictive maintenance is a journey, not a one‑off project. GB18 embeds processes, training and governance that keep models accurate and stakeholders engaged.

Data Governance & Security

Encrypted pipelines, role‑based access and IEC 62443‑aligned controls protect OT networks from cyber threats while ensuring compliance with industry regulations.

Change Management & Upskilling

Interactive dashboards, digital twins and hands‑on workshops teach engineers to interpret predictions, provide feedback and iterate thresholds, fostering ownership and continuous improvement.

ROI Tracking & Expansion Roadmaps

KPIs such as mean time between failures, unplanned downtime hours and maintenance cost per unit are tracked in real time, presenting clear savings and guiding phased rollouts to new sites and asset classes.