The mind of a machine – Digital Twin | What is a digital twin (2020)

Digital Twin – Digital is the main reason more than half of the companies on the Fortune 500 have disappeared since the year 2000.

Pierre Nanterme, CEO of Accenture.

Introduction

Technical advances also change the way humans produce things.

Starting from the Industrial revolution 1.0(18th century) to the Industrial revolution 4.0, there is a significant transformation regarding the way we produce products.

Credits to the digitization of manufacturing. One such innovation that is very imperative to business today is Digital-Twin. But do you know what is a digital twin?

While the concept of a digital twin was there since 2002, it’s only thanks to the Internet of Things (IoT).

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Digital Twin

What is digital twin?

In simple terms, digital-twins are virtual replicas of physical devices.

They are a virtual model of a product, service or process.

Digital Twins are used to plan the coming time by running simulations before actual devices are built and deployed.

They are also considered as primary aspects for IoT.

The Digital Twin: like Real Thing, but Virtual

It is a bridge between the virtual digital world and physical world. This pairing of the virtual and digital world allows the data analysts to perform analysis of data.

This helps in monitoring the system to identify problems before they even occur, develop new opportunities, and prevent downtime.

The term was found by Dr. Michael Grieves in 2002. NASA was one of the first to use this technology for space exploration missions.

It helps to save a lot of time, effort, and money needed to manufacture equipment for space.

Digital-twin connects the real and virtual world by collecting real-time data from installed sensors. The data collected is either locally decentralized or centrally stored in a cloud.

After evaluating it from data scientists, it is simulated in the virtual copy of the assets.

“After receiving the information from the IoT devices, the parameters are applied to real assets.”

This integration of data in real and virtual representations helps in optimizing the performance of real assets.

Digital-twins can be used in various industries like utilities, Automotive, Construction, and healthcare.”

They are the next big things in the Fourth Industrial Revolution for the development of new products. A digital twin is a digital version of the physical entity.

Digital twin

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It’s the pipeline that enables this technology.


Types of digital twins

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Following are three types –

  • (“DTP”) Digital Twin Prototype – Consists of designs, analyses, and processes to realize a physical product.
  • (“DTI”) Digital Twin Instance – It is the Digital Twin of each individual part of the product after manufacturing.
  • (“DTA”) Digital Twin Aggregate – It is the aggregation of DTIs whose data is used for interrogation about the physical product, prognostics, and learning.

Characteristics of Digital-Twin

Connectivity

This technology enables connectivity between the physical component and its digital version. It’s created with the help of IoT sensors placed on physical devices.

Homogenization

It is homogeneous in nature. Any type of information can be stored and transmitted to its digital version. This , have allowed digital twins to come into existence.

Modular

This technology works in modules. It helps to identify problems or errors in different parts of the machine individually.

Manufacturers can see which components make the machine perform poorly and replace these with better fitting components to improve its efficiency.


Some examples

Following are examples where digital twins are used to optimize machines-


How can this technology improve your business?

After knowing digital twin technology and its characteristics, let’s see its effect on business. The process of manufacturing machines is complex and costly.

Assembling the first prototype from the parts that haven’t been developed or tested together will often cause problems that may require a significant amount of materials and effort.

Nobody wants to be known as the manufacturer of poor and unreliable machinery.

So wouldn’t be it great if you could build your first prototype secure in the knowledge that it already has hours of thorough testing behind it?

Well, then, consider the example of MEVEA . Mevea combines all plans for your machine into a single virtual model called a digital twin.

This includes all the components necessary to build your machine such as the interface to the real control system.

The digital twin that is created is the virtual, physics-based representation of your machine, capable of simulating its behavior and use in real-time.

It will enable us to detect potential problems even before anything is built. You can develop the most intelligent and complex machine with ease.

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A digital twin learns continuously from itself and updates itself from different sources to represent its near real-time status and working condition.

This self-learning system conveys various aspects of its operating condition, from human experts, such as IT pros with deep and relevant industry domain knowledge, from other similar machines and from the larger systems of which it may be a part.

It integrates historical data from past learning to its digital model.


Benefits of Digital-twin

  • Helps companies improve the customer experience by better understanding customer needs.
  • Enhance existing products, operations, and services.
  • Can contribute to driving the innovation of new business.
  • Digital twins offer a real-time look at what’s happening with physical assets, which can radically alleviate maintenance burdens.
  • A digital twin can reduce the operating cost and extend the life of equipment and assets.
  • Can develop the most intelligent and complex machine with ease.

Drawbacks of Digital twin

  • Can unnecessarily increase complexity.
  • There are also concerns about privacy, security, cost, and integration.
  • Because digital twins are based in the cloud and don’t require physical infrastructure, the associated security risks are somewhat lower than with other types of systems.
  • Every time a new connection is made and more data flows between devices and the cloud, the potential risk for compromise increases. Therefore, industries using digital twin technology must be careful not to rush into adoption without assessing and updating current security protocols.

Applications / Real-time uses

Use to manage Assets –

Using digital twin technology to monitor daily operations and examine manufacturing reduces unnecessary damages on machinery.

Therefore it alerts business owners to potential money-saving changes, such as making adjustments in fuel use.

Quick maintenance and fast repair allow companies to maintain a competitive edge by improving overall output.

Testing New Systems before deploying –

Companies can use digital twins to create and test systems, equipment ideas, and service models before investing in its implementation.

If a virtual model proves effective, its digital twin could theoretically be linked to the physical creation for real-time monitoring.

Analyse data to improve Service –

Digital twins also have customer-facing applications which also include remote troubleshooting.

Using virtual models, scientists can conduct diagnostic testing from anywhere and allow consumers through the proper steps for repair instead of blindly relying on default protocols.

Data obtained from these sessions provide valuable insights for future product planning and deployment.


How Digital twin works?

Data Science experts and math experts models and develop a digital twin of a physical product.

They research that product or system whose digital twin has to be made.

They study the underlying mathematics and physics of that object. And later use that data to develop a model that simulates the real object in the digital world.

The virtual entity is made to receive data from IoT sensors attached to the real objects.

It allows twin simulation of the physical object in real-time, in the process offering insights into potential problems and performance.

It can also be designed using a prototype of a real-world object. In this case, the twin can provide feedback as the product is refined.

It can even act as a prototype even before a real product version is built.


Digital-twin providers

Building a digital twin is quite complex, and up till now, there is yet no standardized platform for doing so.

With many emerging technologies, commercial digital-twin offerings are actually coming from some of the largest companies in the IT industry.

For instance, GE developed digital-twin technology internally as part of its jet-engine manufacturing process. It is now also offering its expertise to customers.

Siemen is also another industrial giant heavily involved in manufacturing.

IBM too is marketing digital twins as part of its IoT push, and Microsoft is offering its own digital-twin platform under the Azure umbrella.


How to use Digital-twin?

You can refer this article. It contains a very good article on how to use this technology.


Digital twin market

The market of this technology is increasing in size.

Statistics say there will be billions of things represented by digital twins, a dynamic software model of a physical thing or system, within the coming few years.

These digital versions of the physical world will lead to collaboration opportunities among data scientists whose jobs are to understand.

What data tells us about operations and physical world product experts(Developers and engineers).

This technology helps companies improve the customer experience by better understanding customer needs, develop enhancements to existing products, operations, and services.

We can even help drive the innovation of new business.

For example, GE has a digital twin called “digital wind farm”. It opened up new ways to improve productivity.

GE utilizes the digital environment to inform the configuration of each wind turbine prior to construction.

Its goal is to generate gains in efficiency by analyzing the data from each turbine that is received by its virtual equivalent.

Around 75 percent of digital twins will be integrated with at least five endpoints by 2023.

In the future, visualizing complex systems will require the linking of multiple digital twins.

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Conclusion

Hence digital twin provides a chance to gain a competitive advantage over other companies.

Apart from saving costs, it has a lot of other benefits too. All the above information seems to predict we are on the cusp of a digital twin technology explosion.

More companies will learn of real-world success stories and will want to deploy their very own digital twins to gain a competitive advantage.


In 2019, Gartner once again named digital twins as a top trend, saying that

“with an estimated of around 21 billion connected sensors and endpoints by 2020, digital twins will exist for billions of things in the future”.


Question for today!

Do you think that the technology (platforms) to implement digital twins is already mature enough (i.e. keeping pace with what can be done, and what customers would like to have, etc.)?

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Few thoughts over this.

Digital twins offer strong potential to achieve better insights on their objects and drive better decisions.

Digital twins are the next step in the Internet of Things (IoT) driven world, where CIOs are increasingly leveraging IoT technologies in their digital business journey.

The Digital Twin: Like the Real Thing, but Virtual.


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