Predictive Maintenance Powered by Real-Time IoT Insights
ioX-Connect Predictive Maintenance transforms how organizations manage equipment reliability by combining continuous IoT sensor data with advanced analytics and CMMS automation. The platform detects abnormal trends in vibration, temperature, pressure, and energy usage to predict potential failures before they occur. By connecting condition data directly to automated maintenance plans and triggers, ioX-Connect helps reduce downtime, extend asset life, and optimize maintenance resources — all from one unified dashboard.
From Sensor Data to Automated Maintenance Decisions
ioX-Connect’s built-in analytics engine constantly monitors sensor and equipment data to identify early warning signs of wear, imbalance, or inefficiency. When anomalies are detected, the platform automatically creates alerts or maintenance work orders through its integrated CMMS. This seamless flow between IoT monitoring and maintenance execution ensures reliability, safety, and reduced operational costs.
Continuously analyze vibration, temperature, and other parameters to detect early indicators of asset fatigue or malfunction.
Create maintenance plans triggered by sensor thresholds, run-time hours, or equipment status — minimizing unplanned downtime.
Identify anomalies and trends through built-in analytics and machine-learning-ready data structures for future AI enhancement.
Directly link predictive insights to work orders, planned maintenance, and asset history for end-to-end reliability management.
View condition trends and performance metrics in real time with intuitive dashboards, alarms, and color-coded heatmaps.
Access full sensor histories and trend lines to benchmark performance, validate maintenance strategies, and improve accuracy over time.
Trusted by customers across multiple industries
