What is a digital twin?

A digital twin is essentially a virtual representation of real-world systems, encompassing physical objects, infrastructures, and processes. This can range from individual physical objects, mechatronics systems such as airplane landing systems, entire buildings, cities, or manufacturing processes. The key advantage of digital twins lies in their ability to utilize real-world data to feed the digital replica, making them highly powerful.

Digital twins can follow the physical system throughout its entire lifecycle, from the design and production phases to operation and maintenance. Therefore, digital twins are dynamic models that evolve in real-time with data from the actual system.

Digital twins are typically categorized into three main types: product digital twin, production digital twin, and performance digital twin, encompassing both product and production aspects. Each of these categories fulfills distinct roles in the development and monitoring of the product. Let's explore these roles further:

• Ideation: During the early design phase, engineers utilize product digital twins to simulate and validate designs. This ensures that products meet specified requirements. For instance, engineers can assess whether a ship's propeller meets operational needs or if an aircraft's noise levels comply with regulations. Additionally, they can explore ways to reduce material usage while maintaining operational efficiency. According to studies, product digital twins dominated the market share in 2023.

So, how do we create a product digital twin? It usually starts with a CAD model where we convert the product's geometry into the digital realm. Next, we need to translate its performance characteristics into the digital world to create an integrated digital replica of the physical object. This is achieved through multi-physics simulation with data from real-world for the loading of the physical object and its environmental conditions, data analytics, and machine learning techniques. At FEAC, we strongly believe in the importance of multi-physics simulation, recognizing that various aspects of physics intricately intertwine in nature, including mechanical strength, heat transfer, and electromagnetics. Consequently, multi-physics simulations create highly accurate models.

By analyzing simulation results, we can predict how our system will behave in real-life scenarios. Can our system withstand the loads? Can we implement geometry changes while still meeting load requirements?

Today's products are incredibly complex, leading to a common concern: how can we ensure accurate results?

Although modern products are highly complex, advanced technologies such as Finite Element Analysis (FEA) and Boundary Element Modelling (BEM) can be applied to simplify the analysis. FEA breaks down the system into manageable components, providing a comprehensive understanding of its behavior under various conditions. Additionally, Reduce-Order-Model (ROM) techniques are utilized to reduce computational time and power without compromising accuracy.

The Boundary Element Method (BEM) casts its focus on the perimeters of systems. This surface is meticulously divided into small elemental surfaces or “boundary elements” described by differential equations that need to be solved. The differential equations are expressed only for the boundary of the region and not for its interior.

• Realization: The production digital twin plays a crucial role in the realization phase, encompassing all elements from machinery to the entire production line. This comprehensive simulation allows for the identification of errors or failures before actual operations commence. From a business perspective, this capability facilitates cost-effective and customized production processes.
• Utilization: Through the utilization of sensors and data collection, performance or real-time digital twins are created to enable continuous monitoring of products or production processes. A key advantage of performance digital twins is their ability to facilitate predictive maintenance, thereby enhancing operational efficiency and minimizing downtime.

Why are digital twins so popular?

• Digital twins can predict the performance of our system before even constructing it.
• We can explore numerous "what-if" scenarios and make necessary adjustments to our product, such as redefining geometry or material selection.
• We can observe how our system responds under various operating conditions, including extreme scenarios.
• We can iterate quickly in the design process compared to using physical prototypes.

What benefits can digital twins bring to an organization?

• Enhanced collaboration between different parts of the organization.
• Real-time monitoring enables companies to continuously engage with systems and meet market demands while controlling costs.
• Cost reduction by minimizing the need for physical prototypes and accelerating the design phase.
• Facilitated innovation by allowing exploration of multiple designs and "building" ideas within the digital twin environment.
• Accelerate time-to-market by iterating more rapidly between design phases.

?For a decade, our company has been deeply involved in the digital twin industry, integrating this technology across multiple sectors. Through our extensive experience, we have seen the significant capabilities that digital twins offer organizations in achieving their business goals.

We hope you enjoyed this article, offering just a glimpse into the vast potential of digital twins!