Remote Predictive Maintenance System

In the industrial sector, equipment maintenance is often conducted based on time schedules or preventive maintenance cycles, which can lead to unnecessary costs and downtime. As equipment ages, unexpected failures become more likely, making time-based maintenance inefficient and costly, potentially causing unplanned downtime. Predictive maintenance addresses these issues by enabling real-time condition monitoring of equipment. It involves techniques to accurately monitor the current condition of machines or any industrial equipment, aiming to predict upcoming failures 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 necessary.

In this remote predictive maintenance design, data on key parameters like vibrations, acoustic signals, temperature, humidity, and other parameters are evaluated and processed by an AI algorithm that forecasts equipment failures before they occur. The system uses secure connectivity options such as LTE-M, Narrowband IoT (NB-IoT), and secure Message Queuing Telemetry Transport (MQTT) to transmit data to a dashboard where supervisors can visualize machine health and receive alerts if maintenance is required. This allows for maintenance to be performed as needed, significantly reducing unplanned downtime and minimizing service calls.

System Benefits:

• Remotely visualize the health state of every pump or motor via a web browser, enabling real-time monitoring, reducing unnecessary service calls, maximizing equipment uptime, and allowing operators to track equipment status and make informed decisions.
• A convenient GUI for commissioning, local data transfer, and firmware updates via Bluetooth^® simplifies system setup and allows for quick deployment, minimizing system disruption.
• Embedded AI algorithms can be updated remotely to further enhance features, ensuring continuous optimization of predictive maintenance capabilities and allowing for real-time improvements without on-site interventions.
• Rich connectivity features such as LTE-M, Bluetooth, Ethernet 10/100Mbit, USB, and CAN enable integration into various industrial environments and infrastructures.