Fix Equipment Before It Breaks — Not After
AI-powered predictive maintenance uses sensor data, machine learning, and equipment history to identify failure precursors days or weeks before they cause downtime — enabling planned maintenance that minimizes disruption and eliminates the emergency repair costs that scheduled maintenance can't prevent.
What RLM Delivers on Predictive Maintenance
Traditional maintenance strategies — run-to-failure and time-based scheduled maintenance — both produce excess downtime and cost. Predictive maintenance, enabled by AI, targets maintenance interventions at the moment they're needed — preventing failures before they occur without over-maintaining equipment that doesn't need service.
How We Approach Predictive Maintenance
We work Predictive Maintenance the same way each time: establish the baseline, test the market properly, negotiate on evidence, and stay involved through implementation.
Maintenance Cost Baseline & ROI Assessment
We establish your current maintenance cost baseline — planned maintenance cost, unplanned downtime frequency and cost, emergency repair spend — and model the ROI of predictive maintenance against your specific failure modes.
Sensor & Data Architecture Assessment
Predictive maintenance requires sensor data from the equipment being monitored — vibration, temperature, current draw, acoustic emissions, and others. We assess existing sensor coverage and design the instrumentation additions needed for each target failure mode.
Platform Evaluation
We evaluate predictive maintenance platforms — Samsara, SparkCognition, C3.ai, Aspentech, GE Digital Predix, and others — against your equipment types, sensor data sources, and CMMS integration requirements.
Model Development & Validation
Predictive models must be trained and validated on your equipment's specific failure history and operating conditions. We design the model development process that achieves production-grade prediction accuracy.
Predictive Maintenance Selection Criteria
These are the dimensions we have seen separate a Predictive Maintenance deployment that works from one that quietly becomes shelfware.
Prediction Lead Time
How far in advance does the platform predict failures? The longer the lead time, the more flexibility maintenance teams have to plan interventions. Evaluate against your typical spare parts lead times and maintenance scheduling cycles.
False Positive Rate
Predictive maintenance that generates too many false alarms creates maintenance backlog without preventing real failures. Evaluate false positive rates and the organizational cost of acting on incorrect predictions.
Fault Type Coverage
Different failure modes require different sensor types and detection algorithms. Evaluate how comprehensively the platform covers the specific failure modes most costly in your operation.
Integration with CMMS
Predictive alerts must create work orders automatically in your CMMS — Maximo, SAP PM, Infor, or others — with the diagnostic context technicians need to arrive with the right parts and tools.
Cold Start Performance
For equipment without failure history, predictive models must generalize from physics-based models or similar equipment fleets. Evaluate cold start capability for new equipment and equipment that rarely fails.
Total Cost of Sensor Instrumentation
Additional sensors are often required for comprehensive predictive coverage. Evaluate the full instrumentation cost — sensor hardware, installation, connectivity, data ingestion — as part of the total solution TCO.
"What set RLM apart was that they didn't have a preferred answer. They evaluated our options honestly and told us what they actually thought."
We are paid by the provider you choose, which means we have no reason to steer you toward any particular one.
Where This Matters Most
Sector-specific considerations we see repeatedly in ai and automation engagements.
A Sample of the AI & Automation Providers We Evaluate
RLM is vendor neutral. These are among 600+ providers in our evaluation set — inclusion here is not an endorsement, and we are paid by the provider you choose, not by any provider in particular. How that works →
Where Do You Want to Start With Predictive Maintenance?
Start with a no-cost conversation with an RLM AI advisor — vendor neutral, no agenda, just clarity.
Speak to an Advisor