At present, maintenance is often preventive and time-based rather than based on actual equipment conditions and predictive methods, and this results in unnecessary maintenance costs and causes unanticipated downtime.
Predictive maintenance describes a set of techniques to accurately monitor the current condition of machines or any type of industrial equipment, with the goal of predicting upcoming machine failure by using automated quasi-real-time analytics and machine learning. This approach promises cost savings over routine or time-based preventive maintenance because tasks are performed only when needed.
In the Remote Predictive Maintenance solution, the evaluation of vibrations, acoustic signals, temperature, humidity, and further parameters is implemented by an artificial intelligence (AI) algorithm and transmitted to a dashboard via LTE-M or NB-IoT and secure MQTT, alerting the supervisor via a web browser if any maintenance is required before failure occurs.
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SmartBond TINY™ Bluetooth® Low Energy Module
|Bluetooth® Low Energy||Buy / Sample|
LTE Cat-M1 Cellular IoT Module for Global Deployment
|Cellular IoT Modules||Buy / Sample|
200MHz Arm® Cortex®-M33 TrustZone®, Highest Integration with Ethernet and CAN FD
|RA Arm® Cortex®-M MCUs||Buy / Sample|
128Mbit, 2.7V Minimum SPI Serial Flash Memory with Dual I/O Support
|SPI NOR Flash||Buy / Sample|
Wide VIN 1.2A Synchronous Buck Regulator
|Buck Regulators (Integrated FETs)||Buy / Sample|
1.2A High Efficiency Buck-Boost Regulators
|Buck-boost Regulators (Integrated FETs)||Buy / Sample|
Low Noise LDO with Low IQ, High PSRR
|Linear Regulators (LDO)||Buy / Sample|
High-Performance Relative Humidity and Temperature Sensor
|Humidity & Temperature Sensors||Buy / Sample|