Digital Twin Applications in Industry 4.0

Applied Tech Review | Monday, July 04, 2022

Businesses using digital twins can reap significant benefits, such as enhanced operations, product and service innovation, and shorter time-to-market.

Fremont, CA: In recent years, as the Internet of Things (IoT) has become increasingly prevalent, there has been much interest in digital twins. A digital twin is a virtual representation that matches the lifecycle of a physical object or process. This technology provides a near real-time link between the physical and digital worlds, enabling remote monitoring and control of equipment and systems. In the end, it can execute simulation models in order to test and predict asset and process changes under various scenarios.

Digital twins applications in Industry 4.0

Process planning and optimization

A digital footprint can thoroughly analyze important KPIs such as production rates and scrap counts by collecting sensor and ERP data from a manufacturing line. This facilitates the identification of the root cause of any inefficiencies and throughput losses, optimizing yields and minimizing waste. Rich, integrated historical data on equipment, processes, and environments can further improve production scheduling by enabling downtime forecasts.

Predictive maintenance

By gaining a comprehensive perspective of the health and performance of their equipment, businesses may spot anomalies and deviations in their operations quickly. Maintenance and replacement of spare parts can be scheduled proactively to reduce time-to-service and prevent expensive asset breakdowns. Predictive maintenance utilizing Digital Twins can generate a new service-based revenue stream for OEMs while enhancing product reliability.

Product design and virtual prototyping

Virtual models of items in use provide full insight into usage patterns, deterioration points, workload capacity, defect occurrence, etc. By gaining a deeper grasp of a product's characteristics and failure mechanisms, designers and developers may accurately assess a product's usability and enhance the design of future components. Similarly, original equipment manufacturers (OEMs) can adapt their offers for distinct consumer groups depending on usage patterns and product deployment scenarios. Digital twin technology also facilitates the creation of virtual prototypes and the execution of robust simulations for empirical data-driven feature testing.

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