Digital Twin of an Automotive Brake Pad for Predictive Maintenance

Abstract The traditional manufacturing industry is being challenged globally with the comprehensive growth in digital technologies and big data. Digital Twin (DT) technology is one such vision that refers to a comprehensive physical and functional description of a physical component, product or an entire system with all the operational data. The Digital Twin of a product establishes a physical-virtual connection that paves way to real time monitoring all through the entire life cycle of the related product. This paper describes the advance of a digital twin that supports in the predictive maintenance of an automobile brake system. As a proof of concept, brake pressure was measured at different vehicle speeds using ThingWorx Internet of Things (IoT) platform. The data captured using the platform was used to demonstrate the prediction of brake wear using the CAD model implemented in CREO Simulate.