Quick solutions for intelligent condition monitoring

The Industrial Internet of Things (IIoT) is still in its early stages of implementation, but the potential for increased productivity and lower equipment ownership costs is clear. One way for companies to begin exploring the benefits of IIoT is through the implementation of intelligent condition monitoring.


Condition monitoring involves continuously assessing the health of equipment and individual components, and using this information to transform traditional maintenance policies. Instead of waiting for faults to occur or replacing parts at pre-determined intervals, predictive maintenance can be used to replace parts only when necessary, reducing equipment downtime and eliminating the need for excessive spare parts inventory.


One way to implement condition monitoring is through the use of sensors attached to equipment, which can provide information on motor speed, load torque, voltage, and current, as well as additional data such as vibration and temperature. By combining this data and analyzing it in the right way, companies can detect abnormal conditions such as bearing wear or imbalances.


However, implementing condition monitoring can be a daunting task for companies that may not have the necessary data science skills and analytics tools. One solution is to infuse artificial intelligence (AI) into the process, using machine learning techniques to analyze the data and detect unusual performance. Avnet has created a multi-sensing module with an integrated machine-learning core (MLC), which simplifies the use of machine-learning techniques for predictive maintenance and includes built-in wireless connectivity for easy prototyping and testing.


Another important aspect to consider when implementing condition monitoring is power management and security. The STMicroelectronics wireless industrial node (STWIN) module includes an embedded secure element and lithium-ion battery charger, and supports various forms of connectivity including Bluetooth Low Energy, Wi-Fi, and cellular.


Avnet also offers cloud-based condition monitoring and tracking tools, which allow users to view equipment status in real-time and manage assets remotely. These tools simplify the process of detecting anomalies and creating a predictive maintenance plan to minimize downtime and boost productivity.


In conclusion, thanks to the availability of modular IoT sensing nodes and ready-to-use software packs, intelligent condition monitoring is a quick and effective way for companies to begin exploring the benefits of IIoT. Implementing a modular condition-monitoring solution can deliver powerful results that demonstrate the value of IIoT applications and can strengthen the case for committing to additional and more ambitious projects.

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