Infineon Technologies AG (FSE: IFX / OTCQX: IFNNY) launches the new XENSIV™ Predictive Maintenance Evaluation Kit, which was co-developed with the IoT service provider Klika Tech and is powered by the cloud service provider AWS to offer an end-to-end solution for customers. The kit includes hardware (sensors, microcontroller, embedded security), software as well as CloudFormation templates. It represents a perfect starting point for quick and easy evaluation of sensor-based condition monitoring and predictive maintenance – proving that Infineon makes the IoT work. The target applications involve heating, ventilation and air conditioning (HVAC) equipment as well as motors, fans, drives, compressors, refrigeration and other components of Smart Buildings.
“Together with AWS and Infineon we assembled an end-to-end HVACR predictive maintenance evaluation kit and anomaly detection solution that enables building operators to evaluate features to proactively respond to issues before they become costly failures,” said Gennadiy Borisov, President and Co-CEO of Klika Tech. “There is now a complete evaluation solution to increase efficiency and reduce system downtime – all in a scalable evaluation platform that can be deployed quickly.”
“With the rise of Smart Buildings, features such as condition monitoring and predictive maintenance become increasingly important to leverage the full potential of intelligent buildings,” said Robert Junker, Head of Emerging Applications at Infineon. “This evaluation kit allows customers to easily evaluate sensor-based condition monitoring and predictive maintenance features in their HVAC systems. Together with our partners, we can now provide them full end-to-end support along their predictive maintenance journey.”
The XENSIV Predictive Maintenance Evaluation Kit is an extension for the XMC4700 XMC™ Relax Kit. It can be equipped with XENSIV sensor satellite boards with a broad range of sensors for data collection and condition monitoring such as:
- Airflow measurement at the compressor based on the XENSIV DPS368 barometric pressure sensor
- Current measurement at the fan and compressor based on the XENSIV TLI4971 current sensor
- Position sensing of the motor with XENSIV TLI493D-W2BW 3D magnetic sensor
- Sound anomaly detection in the unit with the XENSIV IM69D130 MEMS microphone
- Linear movement vibration measurement with XENSIV TLE4997E Linear Hall sensor
- Opened and closed lid detection with XENSIV TLE4964-3M Hall sensor
- Speed and direction measurement with XENSIV TLI4966G Double Hall sensor
- Data processing with XMC™ industrial microcontroller XMC4700 powered by Arm ® Cortex ®-M4
- Secured connection and authentication as well as multi-account registration with OPTIGA™ Trust M embedded security solution.
The software provided fully supports the FreeRTOS kernel. AWS Cloud integration is completed by full AWS CloudFormation templates and a software application stack. A Graphic User Interface (GUI) and basic anomaly detection are also included. For connectivity Wi-Fi and Ethernet are integrated on-board, as well as a mikroBUS™ ClickBoard interface for extended connectivity. Multi-account registration is supported with OPTIGA Trust M embedded security solution.
According to IHS Markit, the overall Smart Building market will be worth 17.5 billion USD in 2022. Coming from Smart Factories, predictive maintenance techniques are one of the key features of Smart Buildings. Predictive maintenance can lead to 70 percent fewer breakdowns and 25 percent fewer maintenance costs, while well-maintained equipment can extend its lifetime by 20 percent. Especially HVAC end-users such as building owners and facility managers request predictive maintenance functionality in their equipment since the failure of equipment can result in severe disruption of a building’s operations.