WearVue, a revolutionary color-coded wear monitoring system, is transforming the mining industry by simplifying wear monitoring and ensuring the system is both scalable and environmentally sustainable.
The system, developed by Glenn Brearey and Matt Rigby, utilizes a patented Green-Yellow-Red color-coded system to provide intuitive visual feedback on wear levels. This simple yet effective approach allows for quick and accurate assessments of wear patterns, eliminating guesswork and reducing downtime.
WearVue's capabilities are further enhanced by the addition of VueVision, an IoT-enabled platform powered by AI. VueVision transforms wear monitoring into a data-driven process, delivering real-time predictive analytics that help companies shift from reactive maintenance to proactive strategies.
WearVue's color-coded system is designed to be both accessible and scalable, with its current system providing intuitive three-color visual feedback for human operators. However, the addition of AI-powered tools takes its potential even further, enabling advanced automation and greater efficiency.
For example, an AI camera pre-trained for WearVue could be installed at a truck dump to monitor the sensors during tipping. If the camera can't see the green or yellow dots it saw previously, it means a hang-up in the tray is blocking the view of the sensors. In such cases, the AI-enabled system could trigger a robotic water cannon to wash a specific area, rather than cleaning the entire tray.
WearVue's journey as an emerging start-up has been bolstered by key collaborations with Evolve Group, SFDesign, Loctite, and Curtin University.