AI-Based Predictive Maintenance
Short answer. AI-based predictive maintenance uses sensor data, operating conditions and maintenance history to estimate failure probability and remaining useful life for each asset, so maintenance is planned on condition rather than on a calendar. Results flow into the CMMS as recommendations for planners.
AI/ML Guides
What problem does this solve?
Calendar-based maintenance wastes healthy components and still misses failures.
What does the architecture look like?
How does it work?
Few failures? Start with anomalies
Anomaly detection learns normal behaviour and flags deviations, useful before failure history accumulates.
Remaining useful life
Survival and degradation models estimate time to failure as history grows.
Into the workflow
Predictions only create value when they become planned work in the CMMS.
Implementation considerations
- Clean and standardise failure codes.
- Agree thresholds with planners based on cost of downtime.
Frequently asked questions
Which assets to start with?
Critical assets with existing sensors and costly unplanned downtime.
Related solutions
Predictive Maintenance
AI-based predictive maintenance estimates the probability and timing of equipment failure from sensor data, operating conditions and maintenance history, so work is planned before a breakdown.
SolutionAI & Machine Learning
AgenticNex AI builds machine learning systems for prediction, anomaly detection, computer vision and optimisation, engineered for production rather than demonstration.
More in the Predictive Maintenance guide
Knowledge Graph + AI for Industrial Asset Intelligence
Combining a knowledge graph with AI gives industrial asset intelligence both context and prediction.
AI/ML GuidesPhysics + Machine Learning for Industrial Risk Detection
Physics-informed machine learning combines physical models, such as flow balance or torque and drag, with data-driven models that learn the residuals physics cannot explain.
Discuss Your AI Challenge
Talk it through with an engineer who builds these systems.
Discuss Your AI Challenge