Digital twins enable engineers to create virtual prototypes of platforms or components, allowing for rapid iterations and testing by simulating various scenarios and assessing different design options performance before physical prototypes are built, reducing development time and costs.

By connecting the digital twin to real-time data from sensors embedded in products, manufacturers can monitor overall attributes. This data can be used to analyze and optimize the design, identify potential issues, and make informed decisions for improvements.

By integrating real-time data from the production line, manufacturers can monitor quality, detect defects, and make adjustments in real time, improving overall product quality.

Digital twins can predict maintenance needs and potential failures by continuously monitoring the product's condition through sensor data. This enables proactive maintenance, reducing downtime and optimizing the lifecycle of the product.

Digital twins can be extended to include the entire supply chain, providing visibility and transparency across the network. This enables manufacturers to optimize inventory, track components, and streamline logistics, reducing costs and improving overall efficiency.

Digital twins can gather data from connected products/platforms in the field to understand how customers use them and identify potential areas for improvement. This information can be used to develop personalized features and services, enhancing the overall end user experience.