3 Digital Twin Applications For Industry 4.0

Applied Tech Review | Wednesday, May 04, 2022

Companies that use digital twins can reap significant benefits such as improved operations, product and service innovation, and faster time-to-market.

FREMONT, CA: A digital twin is a virtual model that mimics the behavior of a physical object or process throughout its lifecycle. This technology allows you to remotely monitor and control equipment and systems by providing a near real-time bridge between the physical and digital worlds. Finally, it can run simulation models to test and forecast assets and process changes under various "what-if" scenarios.

Creating a Digital Twin Necessitates Several Steps, Including:

• Sensors that record the operational behaviors of assets and processes (vibration, temperature, pressure, etc.) and their operating environments (air temperature, humidity, etc.)

• Communications networks that transfer data from physical devices to the digital world securely and dependably.

• A digital platform that acts as a modern data repository, gathering and storing shop floor sensor data alongside high-level business data (e.g., MES, ERP). By combining these data sources, actionable insights for data-driven decision-making can be derived – using advanced AI/machine learning algorithms.

3 Digital Twin Applications for Industry 4.0

Digital twin technology provides unprecedented visibility into assets and production, allowing for identifying bottlenecks, streamlining operations, and developing innovative products. The three major applications of digital twins for Industry 4.0 are listed below.

Predictive Maintenance: Spare part maintenance and replenishment can be planned to reduce time-to-service and avoid costly asset failures. Predictive maintenance using Digital Twins can provide OEMs with a new service-based revenue stream while improving product reliability.

Process Planning and Optimization: A digital footprint ingesting sensor and ERP data from a manufacturing line can greatly analyze important KPIs such as production rates and scrap counts. This aids in determining the root cause of any inefficiencies and throughput losses, optimizing yields, and reducing waste.

Product Design and Virtual Prototyping: Virtual models of in-use products provide detailed insights into usage patterns, degradation points, workload capacity, defects, etc. Designers and developers can correctly evaluate product usability and reliability by better understanding a product's characteristics and failure modes.

The best way to start a Digital Twins initiative is to identify the asset(s) and processes with the greatest potential for value creation and then start with a pilot implementation. A digital twin should be a work-in-progress that evolves and scales in real-time as your IT capacity grows and matures. Digital twins of different components are typically interconnected to form a large, composite twin of a highly complex machine or process.

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