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Connected Equipment Predictive Maintenance

by Trackonomy

The Sentient Platform organizes asset health, identifies developing failure risk.

Trackonomy
Industry
Transportation & LogisticsIndustrial & ManufacturingWarehouses & Supply ChainManufacturing
Use cases
Condition MonitoringPredictive Maintenance
Deployment
Public SaaSEdge/Local
Services
InstallationSystem IntegrationSupport & MaintenanceData AnalyticsSoftware Platform
Available in
United StatesMexicoEstoniaIndia
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The challenge

What operators are up against

Operators responsible for industrial machines, production equipment, operating conditions, service histories, and maintenance teams cannot continuously inspect every operating condition or developing fault. Periodic checks leave gaps between readings, while isolated local indicators provide limited history and context. A late response can cause downtime, safety exposure, equipment damage, or incomplete compliance evidence. Teams need timely measurements, clear exceptions, and a defined operating response.

The solution

How Connected Equipment Predictive Maintenance addresses it

Connected Equipment Predictive Maintenance combines Trackonomy connected labels or devices, supported mobile and fixed readers, and the Sentient Platform for continuous physical operating evidence. Configured rules associate events with the relevant asset, shipment, equipment, or workflow and identify conditions requiring attention. Authorized teams receive current status, history, and exception alerts so they can intervene while the operating outcome can still be protected.

How it works

A project team defines the monitored assets, locations, expected movements, operating thresholds, users, and response rules, then installs the selected Trackonomy labels, devices, mobile readers, or fixed readers. Field components capture identity, location, movement, status, and supported condition events and pass them through the configured radio and edge path. The Sentient Platform associates each event with its operating context, preserves history, evaluates rules, and raises exceptions. Authorized operations staff review the evidence, complete the required intervention, and use recurring patterns to improve the workflow.

AnalyzePublic SaaS / Edge/Local platform
ActInstallation, System Integration, Support & Maintenance, Data Analytics, Software Platform

Vendor documentation: vendor website

Evidence level: L1 · Vendor-stated: how evidence levels work

Why teams choose it

Field data capture

Components capture identity, location, movement, status, and supported condition events around the monitored asset, shipment, equipment, or workflow

Supported data exchange

Trackonomy devices and readers use the supported multi-radio path for each deployment; no single public transport applies to every configuration

AI-assisted analysis

The Sentient Platform organizes asset health, identifies developing failure risk, and routes prioritized maintenance evidence

Operational response

Inspect priority equipment, schedule corrective work, reduce unplanned stops, and review recurring failure patterns

Deployment context

Designed for manufacturers, industrial operators, utilities, and maintenance organizations across individual production assets, facilities, and multi-site equipment fleets

Role-based visibility

Authorized users can review current status, history, and operating exceptions

Prerequisites

Limitations / not covered

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