Digital Twin Technology.

 What is digital-twin technology?

A digital twin is a digital replica of a physical object, person, system, or process, contextualized in a digital version of its environment. Digital twins can help many kinds of organizations simulate real situations and their outcomes, ultimately allowing them to make better decisions.

What are the benefits of digital twins?

Improved performance

Real-time information and insights provided by digital twins let you optimize the performance of your equipment, plant, or facilities. Issues can be dealt with as they occur, ensuring systems work at their peak and reduce downtime.

Predictive capabilities

Digital twins can offer you a complete visual and digital view of your manufacturing plant, commercial building, or facility even if it is made up of thousands of pieces of equipment. Smart sensors monitor the output of every component, flagging issues or faults as they happen. You can take action at the first sign of problems rather than waiting until equipment completely breaks down.

Remote monitoring

The virtual nature of digital twins means you can remotely monitor and control facilities. Remote monitoring also means fewer people have to check on potentially dangerous industrial equipment.

Accelerated production time

You can accelerate production time on products and facilities before they exist by building digital replicas. By running scenarios, you can see how your product or facility reacts to failures and make the necessary changes before actual production.

How does a digital twin work?

A digital twin works by digitally replicating a physical asset in the virtual environment, including its functionality, features, and behavior. A real-time digital representation of the asset is created using smart sensors that collect data from the product. You can use the representation across the lifecycle of an asset, from initial product testing to real-world operating and decommissioning.

Digital twins use several technologies to provide a digital model of an asset. They include the following.

Internet of Things

Internet of Things refers to a collective network of connected devices and the technology that facilitates communication between devices and the cloud as well as between the devices themselves. Thanks to the advent of inexpensive computer chips and high-bandwidth telecommunication, we now have billions of devices connected to the internet. Digital twins rely on IoT sensor data to transmit information from the real-world object into the digital-world object. The data inputs into a software platform or dashboard where you can see data updating in real time.

Artificial intelligence

Artificial intelligence (AI) is the field of computer science that's dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem solving, and pattern recognition. Machine learning (ML) is an AI technique that develops statistical models and algorithms so that computer systems perform tasks without explicit instructions, relying on patterns and inference instead. Digital twin technology uses machine learning algorithms to process the large quantities of sensor data and identify data patterns. Artificial intelligence and machine learning (AI/ML) provide data insights about performance optimization, maintenance, emissions outputs, and efficiencies.

Digital twins compared to simulations

Digital twins and simulations are bothvirtual model-based simulations, but some key differences exist. Simulations are typically used for design and, in certain cases, offline optimization. Designers input changes to simulations to observe what-if scenarios. Digital twins, on the other hand, are complex, virtual environments that you can interact with and update in real time. They are bigger in scale and application.

For example, consider a car simulation. A new driver can get an immersive training experience, learn the operations of various car parts, and face different real-world scenarios while virtually driving. However, the scenarios are not linked to an actual physical car. A digital twin of the car is linked to the physical vehicle and knows everything about the actual car, such as vital performance stats, the parts replaced in the past, potential issues as observed by the sensors, previous service records, and more.

What are the benefits of digital twin technology?

• Enhance supply chain agility and resilience 

Supply chain disruptions have put a spotlight on agility and resilience. A combination of emerging technologies and platforms have made it possible to pursue a digital twin of the physical end-to-end supply chain. With this type of digital twin, companies get visibility into their supply chain, such as lead times, and can make real-time adjustments internally and with their partners.

• Reduce product time to market

With digital twins, companies receive continuous insights into how their products are performing in the field. With these insights, they can iterate and innovate products faster and with more efficiency.

• Enable new business models (i.e., product as a service)

Digital twins sometimes have a secondary benefit if you’re able to think about the possibilities. With more data visibility into products, there could be opportunities for subscriptions and offerings that deliver enhanced service or support to customers.

• Increase customer satisfaction 

Digital twins can support improved customer satisfaction though use cases like predictive maintenance, but because they collect real-time data on the product, they can also enable smoother customer service and repair operations, while informing future product improvements.

• Improve product quality

This benefit comes with time and data collection through digital twins. After initial investments have been made, generational improvements of a product—based on real-world operational data from many digital twins—can inform engineers and designers when developing a new product or version.

• Drive operational efficiency

Digital twins offer the insights necessary to gain those operational efficiencies across the value chain. With process-based digital twins, for example, organizations can bring together different data sets to capture real-time information on asset and production performance. Not only can they see where there might be bottlenecks, but also how potential solutions could impact the overall process.

• Improve productivity

The challenge of employee turnover and retention is nearly universal across industries. When a skilled employee leaves, they almost always take their knowledge with them, creating a barrier that slows productivity. With digital twins, organizations can mitigate some of these challenges through remote monitoring and assistance.

• Inform sustainability efforts

There are opportunities across the value chain to identify sustainability opportunities with digital twins. It can mean swapping out product materials for more sustainable options, reducing carbon emissions or scrap in the manufacturing process, or decreasing the number of service truck rolls.

• Increase data visibility

Digital twins can break down data silos across the enterprise and unlock value across the product (or process) lifecycle. Historical data and real-time data all live in one place.