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Accenture lists' digital twins' in its top technology trends for 2021. It should come as no surprise that 'digital twins' are on that list. 

Digital twins allow companies to see how a new product will perform before releasing it to market by modeling it digitally with all its components, in days instead of months or years.  

By giving them the ability to test products virtually before releasing them to market, digital twins have reduced costly mistakes and increased revenues exponentially for numerous industries, including aerospace, manufacturing, and oil & gas production!

"Digital transformation" is the new way of thinking about coordinating product lifecycle management.  Recent advancement in data integration, AI and IoT has extended digital benefits into physical products. 

As mentioned by Accenture Technology Labs Managing director Michael Blitz, business owners acknowledge the benefits and embrace them across multiple departments. 

Accenture lists’ digital twins as one of the top five technology trends in 2021 because organizations have begun to figure out how to take advantage of the benefits of digital twins in terms of efficiency and convenience at scale.

Unilever sets up 8 Digital Twins in its Consumer Goods Factories: 

Unilever used an outdated control system for its machines, which can only provide essential monitoring of a machine's performance, capabilities, and history of operation. The new digital twinning solution in Unilever factories will analyze their data in real-time to predict future issues with maximum accuracy. 

It provides them with greater transparency into how each piece of equipment works within the factory and consequently allows them to have better planning regarding maintenance needs. 

Unilever hopes that this transformation will help it double profits while simultaneously reducing operational costs through improved workforce productivity rates and increasing revenue from existing assets rather than investing in new facilities or services. 

Accenture lists' digital twins'

What Challenges do Enterprises face while using Digital Twins

Although the digital models themselves are becoming more advanced, sharing these creations across applications is still trickier.

PLM vendors optimize different types of applications for specific use cases. As a result, PLM vendors like Siemens have been buying up and building rich ecosystems that facilitate the exchange of digital twin data across product lifecycles.

Read more: What is Digital Twin Technology, and Why is It Essential for Businesses?

Passing digital twin models is difficult when enterprises buy tools from one vendor. In addition, the lack of integration between apps across different vendors makes the task more challenging.

Various standards groups have been working to help streamline this process. For example, the International Standards Organization has been developing multiple standards for digital twin manufacturing, reducing data loss during exchanges, and promoting business collaboration.

Michael Finocchiaro, a senior technologist at digital transformation consultancy Percall Group, said:

“Without practical implementations from industry leaders like Dassault's 3DEXPERIENCE, PTC Windchill, and Siemens Teamcenter--it will be difficult for brands in various industries such as automotive manufacturing and oil & gas to take full advantage of their new capabilities."

But the jury is still out on how committed vendors are to ensuring interoperability in practice. For example, Finocchiaro said that integrating bill-of-material data across platforms often requires extensive customization despite standards."

Evaluation of this statement would be complete only after an impartial and independent research organization conducted a comprehensive survey with no bias towards any particular vendor or product line. 

Nevertheless, the results from such a study could shed light on whether there truly exists widespread commitment among suppliers toward achieving true cross-platform compatibility and what specific factors lead certain companies down different paths when implementing their unique design strategies.

Despite the rhetoric of openness from companies like Apple, Amazon, and Google when it comes to their customer base, digital twins are expected to put a bit of drag into standards adoption. However, digital twin integration is vital so that stakeholders who work on these platforms can better communicate how they should function in practice.

Industry collaborations like the Object Management Group's (OMG) Digital Twin Consortium could help. Digital Twin Consortium CTO Dan Isaacs said, "While there is a lot more work to be done to enable digital twin interoperability, integration and standards that can support sharing, and common practices will provide a foundation."

The group focuses on creating consistency in digital twin technology's vocabulary, architecture, security, and interoperability. It does not develop standards directly but instead helps the different participants flesh out the requirements that will inform measures by organizations like ISO, the IEC, and the OMG.

The Digital Twin Consortium partners with an open-source community called FIWARE. The community curates digital twin reference components for smart cities, industry, agriculture, and energy. This partnership could make it easier to connect multiple digital twins to model city infrastructure or help businesses become more efficient by better understanding their processes.

Digital transformation is still in early adoption, but it's gaining momentum. Seamless integration and best practices across software and hardware are needed to realize this full potential. Digital twin would need coordination of various technologies like AI/ML, modeling & simulation, IoT frameworks to reach their full potential, including industry-specific data protocols.

For example, these efforts involve using satellite imagery and point cloud scanning coupled with AI and ML to identify structures and anomalies tagged or associated with other assets or attributes. As a result, it helps enterprise teams improve pattern identification, giving them a competitive edge over others in their industry.

Isaac believes that the energy and utility sector will see significant adoption of digital twin technology due to its ability to accelerate the renewable transition. Challenges, however, exist in other industries like the medical industry due to harmonizing systems with different protocols.

To gain a competitive advantage, companies should build intelligent twin models of their products and structures. Accenture's Technology Vision 2021 predicts that businesses that start building these twins now will be the ones pushing industries towards an agile future.

Four Technological Growths to Watch Out in 2021:  

In addition to digital twins, other technologies will continue to grow in 2021, including augmented reality (AR), Blockchain technology, and deep learning/artificial intelligence (AI). All three of these have already made waves throughout many industries, but as Accenture predicts, they will only get bigger over time. 

For example, industries use AR for training purposes, such as flight simulators that allow trainees or employees to practice their skills before deploying on actual missions or tasks. Not only does this save lives, but it's also very cost-efficient because mistakes can happen while practicing. As a result, most companies don't need to spend as much money on training instead of when it matters. 

Blockchain can track the movement of goods, whether physical or digital, like software uploaded onto a website. 

Read more: The Future Digital Twin: What Role Will Digital Twin Play in the Next Ten Years?

It increases transparency and makes it easier for users to see where their products come from - which can be especially important in specific industries such as food safety (think about how many people get sick every year because there was something wrong with the food they ate). 

In addition, since Blockchain records events in 'blocks' that cannot be changed once set, this technology prevents fraud and protects businesses and consumers alike. 

Finally, deep learning/artificial intelligence uses big data sets to perform tasks more accurately than humans would do alone by recognizing patterns within those data sets. 

For example, this technology increases accuracy in medical diagnoses, self-driving cars (which are already on the market), and various other industries where there's a heavy reliance on data analysis, such as financial investment firms.

In 2021 we will continue to see these big four technologies become more integrated into our everyday lives.  

Accenture lists' digital twins'

Early Digital Twin Users will lead the Corporate Future: 

The US Air Force can be a great example to highlight a successful use case of the digital twin. The US Air Force has reduced the prototyping period of aircraft from decades to a few years. 

Chevron, an energy corporation, has claimed that the company can save millions of dollars by predicting failures and maintenance problems using digital twins. Companies like Chevron have already seen these great returns on their investments, so we'll likely see more of them in the future. 

Accenture’s prediction on Digital Twin in 2021,  is not surprising because the benefits are tremendous: imagine how much money companies can save by knowing about failures before they happen and prevent them from happening altogether? 

There is no doubt that the digital twin is delivering on its promises. It has become an excellent asset for businesses as it is improving collaboration and workflows across different departments design, sales, and maintenance teams and engineering. 

Traditional processes have led to process and communication gaps that cause delayed product launches, lack of efficiency, and a high cost.

Digital twins will also allow companies to show consumers how their products work before they are released. 

Medical digital twins will transform healthcare and there is no doubt about that. Digital Twin can help doctors and healthcare professionals make better decisions. They can provide insights to improve patient care, reduce errors, and cut costs. 

The digital twin revolution is here, and it will shake up the healthcare industry. Healthcare is a $3 trillion global industry that employs one in ten Americans. The changes coming to this industry will be so pervasive that they'll touch every aspect of our lives. 

For example, some experts predict that by 2020 as many as half of all medical procedures could be performed virtually using 3D printing technology with doctors controlling robots remotely from miles away! 

This post will explore 15 ways medical digital twins will transform the way we deliver healthcare in the future.    

Read on to learn more about this innovative new technology!

1) Identifying Drug Risks: 

Researchers in pharmaceuticals are using digital twins to identify how different drugs could affect people's hearts. It also helps them determine which combinations would be most effective and safe for patients with cardiovascular issues, all while doing it more cost-effectively than manual testing methods can provide. 

Pharmaceutical researchers have already built a basic model covering 23 drug types so far. We don't know whether they will extend this research.

However, we might see new medications coming out faster and cheaper if they do it. In addition, tests will become more accessible by cutting short design, examination, approval, and launch of new drugs.

The best part of it is that it won't raise any safety concerns along the way!

2) Simulate Human Variability

We can build perfect medical devices. However, humans are imperfect. Human bodies are different from each other. Such as bone variations or muscle movement can become an issue for those who rely on medical equipment to function correctly every day.  

Minor variations in human bodies affect the performance and fitness of medical devices. Virtonomy, a medical engineering company, is helping medical equipment makers to simulate human and animal variability in the browser. 

The German company supports medical device manufacturers in the various phases of the product life cycle, from the concept phase to post-market surveillance. 

3) Generating Patient-Specific Digital Twin

The FDA is one step closer to allowing companies the ability to sell the software-as-a a medical device. The idea behind this regulatory framework is generating a patient-specific digital twin from different data sources, including lab tests, ultrasound measurements of your organs or muscles in use-- you name it! 

It will not only help with innovations for current medical equipment but also future treatments like pacemakers, automated insulin pumps, and novel brain treatment procedures where they can optimize specific components based on patients' needs

Not only can these digital twins help doctors diagnose patients more quickly with better accuracy, but they also have the power to predict the things that may go wrong. 

Read more: Is It Possible to Build Digital Twins of Humans?

4) Providing detailed Explanation of the Patient's Health Data

David Talby, the CTO of John Snow Labs, said that digital twins are helping caregivers capture and find information shared across physicians. He spoke about how it can also provide better care for patients who see their primary physician or specialist. 

The doctor might not know about what happened at other appointments with different doctors or nurses who took notes on things like blood pressure readings or actual lab results. So, they will have a baseline understanding of the patient's medical history and medications with this technology. 

A digital twin can offer a more detailed explanation of the patient's health data and present it in an easily digestible way. It uses natural language processing (NLP) and captures all data points concisely with an accurate clinical context for providers.

It means that providers no longer need to sift through lots of different tabs on their computer screens or folders full of paper records, which saves time so they can spend less time searching for relevant information.

medical digital twins will transform healthcare

5) Personalized Health Information

Digital health services are coming into vogue as a result of the pandemic. 

A digital twin allows you to keep up on how healthy you are by tracking symptoms, moods, fitness routines from anywhere in the world using an app!

For example, Babylon Health's App for health checks captures data from patients. It creates digital twin profiles that allow doctors to diagnose them faster than before, vital in combating this deadly virus.

Apple Watch has helped people to use this product for their health needs. The watch provides accurate data. In addition, it can sync with other devices like a heart-rate monitor or GPS device to track information about your mental state. 

6) Medical Digital Twins will transform Healthcare with Genomic Medicine

Swedish researchers have been mapping mice RNA into a digital twin that can help predict the effect of different types and doses of arthritis drugs. The goal is to personalize human diagnosis and treatment using RNA, which will be invaluable in aiding doctors with their decision-making process for complicated patients who may need personalized care.

The researchers have discovered that medication is not as effective at treating patients 40% of the time. Similar techniques are also mapping characteristics of human T-cells to diagnose common diseases earlier when they're more responsive and affordable for treatment, which can help save lives in developing countries where people cannot afford medical care.

7) Predicting Medication with Digital Twins: 

The first step includes collecting data about the patient's age and lifestyle, which helps tailor the digital twin for optimal results with predicting medication effects based on these factors. 

Furthermore, patients can report back if they notice any changes when taking different dosages, so their information can be used as an additional calibration tool for accuracy within this process.

8) Value-Based Healthcare

The rising cost of healthcare is one concern that many nations are trying to combat. One way they're doing this is by exploring new incentive models for how drugs, interventions, and treatments will be valued based on their outcomes--not the costs incurred during production or development. 

The basic idea behind it all is that participants--drug companies among them--will only get compensated proportionate to their impact on those results, encouraging more collaboration with hospitals to produce better care at a lower price than we see today.

Read more: The Future Digital Twin: What Role Will Digital Twin Play in the Next Ten Years?

Imagine a future where your digital twin has all the information about you and can input any decision for possible health concerns. In addition, new types of relationships will be able to form between providers, patients, insurers, and employers as these new 'twins' allow us to create personalized, tailored plans with their help.

9) Better Drug Absorption 

Researchers at Oklahoma State have been working with Ansys to develop a digital twin of the lungs to help them design more effective drug delivery. Unfortunately, they found out only 20% of many drugs reached their target. 

Still, using models and simulations, they were able to redesign how big each pill needed to be for 90% of it to get to its destination-the same place as before and changing the composition so particles could better break down on entry into blood vessels.

10) Whole Body Scanner: 

Q-Bios can be a great example to discuss. Q-Bios is the first clinical digital twin platform that harnessed the ability of digital twins to replicate anything indifferently. 

Q Bios Gemini Digital Twin platform has built Mark-I, a computational biophysics model to scan the whole body. The company reported that Mark- I will examine the human body in 15 minutes and doesn't require radiation or breathe of the actual person. 

Q Bios Gemini has claimed that Mark- I can work 10X better than the traditional MRI scanners for many critical diagnoses. In addition, Mark-I, the computational model, can eliminate bias or hallucination risk from AI and machine learning. 

Another most significant advantage of the Mark-I is that it shields the patients from exposure to too much radiation, protecting them from running into the risks of developing cancer cells in the future. 

Q Bios Gemini has received over $80 million from Andreessen Horowitz and Kaiser Foundation Hospitals to develop and expand its breakthrough whole-body scanning technologies. In the future, the full-body scanning tech from Q Bios Gemini will provide data-driven and affordable care for all.

medical digital twins will transform healthcare

11) Minimizing Risks in Surgeries:  

Medical and software companies collaborate with digital twinning to create exact replicates of human body organs like the heart and the brain. The aim is to minimize risks in critical surgeries and aid organ donations. 

Sim & Cure, a medical technology company, has built a digital twin called Sim&Size. This digital twin simulation will make brain surgery safer for Aneurysms patients as they will need less invasive surgery using catheters to install implants. 

12) Shortening Medical Administrative Protocols: 

Siemens Healthineers has been working with the Medical University of South Carolina to improve hospital efficiency by creating a seamless process for treating stroke patients. 

It is important since early treatment can make all the difference but requires coordination between departments and hospital systems. 

They are implementing new workflow analysis, system redesigns, and process improvement methodologies.

13) Customize New Medical Equipment:  

Philips has developed a predictive maintenance program that collates data from over 15,000 medical imaging devices. Their engineers are using digital twin technology to customize new medical equipment for the needs of different customers.

In addition, it is applying similar principles across all of its medical equipment and hoping this will improve uptime and make things more efficient overall.

14) Virtualized Hospitals

The GE Healthcare Command Center aims to virtualized hospitals and test ideas to determine the best organizational performance. 

With modules for evaluating operational strategy, capacities, staffing models, healthcare delivery models, and managers can experiment with different ideas without risk piloting any one idea.

15) Virtual Organs

The digital transformation of the healthcare industry is breathtaking as well. For example, the use of the Digital Twin in healthcare has helped to develop digital twins of organs and other anatomical structures, personalizing the medical devices to meet the individual needs of patients.

For instance, Dassault Systèmes SE, a French software company, developed a Digital Twin heart using MRI images and ECG measurements. This digital twin of the heart replicates the structure and some functions of the human heart. Now, heart surgeons can feed the patient data into the Digital Twin heart to determine whether the surgery will be successful. 

Dassault Systèmes SE has launched the Living Heart Project in collaboration with academic and industrial members like Philips and Boston. All the Living Heart Project members are working together to build safer and effective cardiac devices for patients. 

The Digital Twin is no longer a hypothesis in the healthcare sector as it's already in use and expanding to make procedures of organ donation and surgery safer. 

Conclusion: 

The medical digital twin concept is an exciting opportunity to improve how we deliver healthcare in the future.

It can help doctors, and healthcare professionals make better decisions, provide insights for patient care, reduce errors, and cut costs.

 What are your thoughts on this new technology? We'd love to hear about them!  

Digital Twins of humans or Digital Me is one of the Hype Cycle for Emerging Technologies.  The term human digital twin may sound like a replica of the actual person. However, it's not the case. 

The human digital twin is the digital version, representing the actual person in real and virtual worlds. In other words, the human digital twin is the virtual identity or persona of the actual person. Not the person himself physically. 

How Do the Digital Twin of Humans Work?  

The human digital twin doesn't have access to the human mind or replicate the actual human being. You may be disappointed to hear this if you are an adventurer. The truth is you will not have a 3D model of your presence in the real world, just beside you. 

The human digital twin is the human model which is present in the cyber world as a database. The database will contain age, weight, sex, education, job, relatives, etc information about you. In addition, the database would also capture abstract human traits like behavior, emotions, and decision patterns.  

To sum it up, it is a digital description of the person stored in the computer, server, or cloud. 

Read more: The Future Digital Twin: What Role Will Digital Twin Play in the Next Ten Years?

The system will add new information to the records as updates about you come into cyberspace. It is important to remember that cyberspace gets your data through your communication on the Internet, 4G, 5G, WIFI, etc., technologies. However, it is not the only source. 

Mobile phones, hospitals, or other institutes obtain your information from time to time. Therefore, your new data will be transferred to cyberspace and stored accordingly. 

Your digital twin model will use complementary technologies like cloud computing and deep learning. The purpose is to provide you feedback information on your diagnoses, health issues, performance, or improvement at work.

Is It Possible to Build Digital Twins of Humans?

Similarities between Digital Twin (DT) and Human Digital Twin (HDT)  

We have mentioned in our earlier posts that Digital Twin builds a connection between the virtual and real world. This post explains that the Human Digital Twin is the digital description of the actual person in cyberspace. So, Digital Twin and Human Digital Twin aren't the same things. 

Despite this fact, there are some similarities between Human Digital Twin and Digital Twin.

1) Both need two-way communications: 

Both are digital models in the virtual environment of their actual product or person. Both will work when developers build a two-way communication path for them. 

Cyberspace needs information about the actual person or the product to analyze and determine predictions. The physical entity will need the projection from cyberspace to make improvements in the real world. 

So, the actual entity and digital replicas are mutually dependent on each other to function correctly. 

2) We need to build the models for both: 

It's a given point but worth mentioning. We need to build the virtual twins of both because DT and HDT are virtual models of the physical entity. The virtual models imitate the behaviors, emotions, functions, traits of the physical commodity. 

So, cyberspace cannot carry out many essential tasks like preparing analysis, summary, and judgment on the input data without the model. On the other hand, the physical entity or the system cannot receive valuable feedback or suggestions from cyberspace. 

3) Both share standard technologies: 

Human Digital Twin and Digital share the standard technologies as listed below: 

We also need to ensure security technology for HDT and DT regarding privacy, reliability, and integrity.

Differences between Digital (Twin DT) and Human Digital Twin (HDT)

There's always been an ongoing debate going on humans vs. machines. Who is winning the race on intelligence, humans or machines? 

Raymond Kurzweil, an American author and Director of Engineering at Google, predicted that machines would achieve human-level intelligence by 2030. We have seen machines and AI doing some fantastic stuff, but humans are still ahead in the race. 

It is at this point where Digital Twin and Human Digital Twin differ from each other. 

Read more: Why Accenture Lists 'Digital Twins' in Top-Five Technology Trends in 2021

Human beings are complex creatures –mentally, physically, and emotionally. So the developers have to detect a few things before building the digital twin of humans. 

They will need to use biosensors and brain-computer science to detect mental activities. For example, blood pressure, respiration, heart rate, hormone levels, and other data will trace mental activities. They will also need to gather data on the objective and subjective reactions based on psychological and human behavioral research. 

There are three main differences between the human digital twin and digital twin: 

1) Humans are complicated creatures, so it's challenging to build virtual twins in cyberspace. On the other hand, digital twins are more accessible to represent in cyberspace because these are just products or systems. 

2) Developers need excellent modeling, data analysis, and data fusion knowledge when building a human digital twin. They also need to focus on physiology, psychology, biology, chemistry, mathematics, and other disciplines for HDT modeling.  In contrast, building digital twins are more uncomplicated as constructions depend on mathematics, physics, chemistry, mechanics, materials science, etc. 

3) We know more about the laws of physics, chemistry, mechanics, etc., so building DT is easier. In contrast, humans are so versatile that most human laws are statistical and not based on solid value. 

Surprising Ways Digital Twin of Humans can help

Creating Digital Personal Assistant

Digital Twin computing can help to expand the scope of human activity into cyberspace from the real world.  The digital twin is the person's digital description, yet it behaves like the actual person in cyberspace. Thus, the digital twin of humans is a great personal assistant in the virtual environment. 

The Digital Twin is the duplicate of the actual person, so it means that a person can work at multiple locations virtually at the same time. 

Creating a dialog with the deceased people: 

Surprisingly, Digital Twin can create dialogs with the dead person, which is impossible in the real world. Thus, we can gain knowledge and experience from the deceased person with the help of Digital Twin. 

Using Digital Twins to interface in cyberspace

It is possible to create a copied version of the human digital twin. Then, provide the clone of the digital twin with abilities and assets that you do not have.

For instance, you can provide the cloned digital twin with language skills you do not have by exchanging or merging with someone else's Digital Twin. 

Bidirectional Brain-Machine Interfaces (BMIs) – the Future of Human Digital Twins 

BMIs can be an excellent example to understand the digital twins of humans. BMIs can alter or monitor the brain and build communication between human and machine interfaces. In addition, BMIs can be used for regular monitoring to pattern the brain's electrical activity without surgical invasion.

 For example, the BMI can tell you that you are inattentive at a specific task which is of great importance. Receiving an alert about your problem ahead of time can help you resolve it before the matter gets to a harmful level. 

The headband BMI can completely change the state of your mind interpreting the electrostimulation in your brain. As a result, experts expect that a growing number of professionals will use it to improve productivity. 

For instance, a BMI headband can apply current to the brain to change the grumpy mood or thrust attentiveness. 

The commercial use of BMI headbands in the future seems promising but also involves social and ethical concerns.  

Is It Possible to Build Digital Twins of Humans?

Conclusion

We have mentioned earlier that the Digital Twin of Humans is hard to build because humans are complex beings. 

The human digital twin has a bright future ahead. The rapid development of computing capacity, cheap intelligent devices, ample data storage, convenient data acquisition, and AI seems to make HDT modeling possible. With our growing ability with digital twin-enabled technology and understanding of ourselves, Human Digital Twin will be the next big thing of the future. 

At present, building a human digital twin may seem like a farfetched idea. However, with time passing by, it will become an achievable goal. Nevertheless, human Digital Twin has a long way to go because the complexity of humans makes modeling and massive data fusion analysis challenging. Moreover, the diversity of data sources, data variability, and heterogeneity are adding to the pressure. 

However, human digital twin development will face backlash from the people due to their worries about safety and privacy. 

It's not a surprise that The European Union and other institutions are trying to impose stricter GDPR and ePrivacy rules. However, the central institutions are aware of the possible threats and trying to keep them under a limit. 

To build successful Digital Twins of humans, we will need to improve our abilities in various fields of research and technology. These fields include social sciences, humanities, natural sciences, applied chemistry, and interdisciplinary. 

We will also need to review other aspects like ethical issues, the reliability of simulation outcomes, and privacy protection if we are using human digital twins seriously. 

The future Digital Twin market holds endless potential as it's becoming a mainstream technology faster. Moreover, the COVID-19 pandemic increased the demand for factory and shop floor automation, real-time planning, and better worker augmentation. Hence, Digital Twin technology is no longer a concept but a necessary solution required for industrial growth.

The fastest-growing digital twin applications will create a high impact in 7 industries and determine how they function in the next ten years - manufacturing, automotive, aerospace, healthcare, retail, oil and gas, and industrial IoT.

The Digital Twin is in its emergence as we've just begun our journey in the Digital Industrial Era. Yet, we can already see tremendous growth and potential that lies ahead.

The Future Digital Twin Market Forecast:

ResearchandMarkets.com reported that about 36% of executives across various industries understand the benefits of digital twinning. So it's good news that 18% of these executives are planning to use it in their operations by 2028.

This increasing demand for intelligent solutions will lead to the rise of digital twin marketplaces. ABI Research reported that the digital twin market would grow from US$3.5 billion in 2021 to US$33.9 billion in 2030 at a 29% CAGR.

Read more: What is Digital Twin Technology, and Why is It Essential for Businesses?

The ABI Research also estimated that the global adoption of digital twins would reach 34.9% by 2026. It's because the future Digital Twin market has such immense potential to support more than 10 million frontline workers in manufacturing. About 35% of manufacturers collect and use data produced by smart sensors to improve manufacturing processes in the USA. 

According to ResearchandMarkets.com, up to 89% of all IoT platforms will include digital twins by 2025. Moreover, Digital twinning will become a standard IoT feature by 2027.

Regional Digital Twin Market Dynamics:

The future Digital Twin market holds prominent shares in various geographical regions around the world. North America has the biggest Digital Twin market and would expand tremendously in the next five years.

Surprisingly, the Asia-Pacific region and Japan will produce lucrative growth opportunities for the digital twin market. It will happen due to a few significant factors:

At present, the USA leads in the adoption of the future digital twins. However, China has the potential to surpass the USA regarding products manufactured using digital twins by 2024.

The Future Digital Twin: What role will Digital Twin play in the next ten years?

What leads North America to Dominate the IoT market globally?

The North American region has two developed economies like the USA and Canada. So, it's no surprise that North America dominates the IoT market in aerospace, automotive, and manufacturing.

These countries heavily invest in developing emerging technologies like digital twins, 3D printing, smart sensors, etc. Moreover, businesses are early adopters of the future digital twin simulation, connectivity, IoT, and AI, into their manufacturing processes.

Manufacturers are upgrading their production methods using connected devices and data flow. In addition, they are using IoT and analytics to operate and boost their companies to remain competitive after the Covid-19 pandemic.

All these factors contribute to the expansion of the IoT market in North America compared to other regions.

Digital Twin Technology Competitive Landscape is Shaped by New Product Launches:

The Digital Twin leaders have launched new solutions to expand their customer base and establish their influence in the industry.

Digital Twin vendors are inclining toward partnerships, mergers, and acquisitions strategies to survive the cut-throat competition. For example, Microsoft Corporation and Ansys Inc agreed to form a joint venture to develop an IoT-enabled digital twin framework in December 2019.

Read more: Is It Possible to Build Digital Twins of Humans?

Bentley Systems Incorporated launched iTwin in October 2019, cloud-based digital twin services to facilitate infrastructure assets and projects. iTwin empowered customers that use two different management software of the company.

Many vendors can provide a few IoT solutions at present. Still, only a few companies are providing customizable end-to-end future Digital Twin solutions, including:

Today's manufacturers are more interested in enhancing their product portfolio by reducing future failures and risks while maximizing productivity. Thus, small and big businesses are tapping into the Digital Twin market to shorten the product launch stages, shaping the competitive landscape.

The Future Digital Twin: What role will Digital Twin play in the next ten years?

Challenges of deploying Digital Twin Technology :

Digital Twin Technology is a framework for building a bridge between the physical and digital worlds. This complex framework of solutions involves prototype design, simulation, manufacturing, assembly, and after-sales service and support. Therefore, manufacturers must satisfy a range of requirements to deploy digital twins successfully, including:

 The biggest challenge of deploying digital twin technology is that it must share the same characteristics as the actual product. With this in mind, the future Digital Twins must have the capabilities to meet some challenges below:

Technological trends of digital twins shaping the future virtual world:

Businesses are interested in exploring the full potential of Digital Twins. They are applying IIoT, semantic technology, VR, and AI in digital twin research. Such experiments are unleashing new technological trends of digital twins shaping the future virtual world that none of us have ever imagined.

Human-Computer Interaction is the New Reality:

One of the newest experimentations of the future Digital Twin includes infusing AR, VR & MR experiences between human and digital twins. In other words, human users will connect with digital twins using senses like sight, sound, touch, and taste.

Semantic Data Modeling in Digital Twin Technology:

The semantic data model structures data logically to give basic meaning to it while highlighting the relationship between them. As a result, it helps to develop application programs quickly. At the same time, it ensures that the applications’ data stays consistent with new updates.

So, semantic technology is used for Digital Twin to improve its design and deployment as follows:

The Future Digital Twin Technology Infused with AI:

Another trending experiment with Digital Twin includes fusing AI through machine learning, big data, service computing, semantic techniques, IIoT, and autonomous robot. The AI fusion enables the digital twin to gain real-time sense and dive into deep learning for many purposes. 

Currently, Digital twins are capable of performing various tasks successfully. Like:

IIoT based sensor technology in the Future Digital Twins:

Many intelligent devices are connected to form systems that monitor, collect, exchange and analyze data in an IIoT network setting. So, IIoT enables Digital Twins to gather and provide input on physical objects using a large amount of data.

It also allows Digital Twins to improve real-time simulation & decision-making capabilities based on analytics focused on multi-channel data.

The Evolving Digital Twin Technology: 

Today's world is witnessing human-to-human, human-to-object, and object-to-object, interactions in everyday lives.  Such interactions between things trigger events and produce states, leading them to certain conditions.

So, the real world is becoming complex due to technological advances often making the collaboration clustering and chaotic.

In this scenario, industries around the globe are integrating IoT and Digital Twins in the manufacturing process to enhance the performance of devices and equipment. Emerging technology is solving many problems that businesses face at present. Surprisingly, the emerging tech will solve the futuristic issues at a higher level that is yet to occur.

Hence, there is no doubt that the businesses using innovative technologies like IoT, Digital Twin simulation, and AI will make them stand out from the crowd.

A decade earlier, this idea of intelligent machines analyzing, reasoning, and making decisions would seem impossible. Also, intelligent machines interacting with each other while transforming the manually operated industrial systems into automated ones were unimaginable.

However, with the future Digital Twin and IoT, that's not the case anymore. According to predictions, by 2020-2030, over 50 billion machines will be connected globally with over seven billion internet consumers.

So, the world will be witnessing another mesmerizing internet transformation in the next ten years with emerging technologies.

Digital Twin Technology is the digital replication of any physical asset or processes used for problem-solving and decision making. The three main components of the digital twin -physical assets, virtual simulation, and connected data- are combined to establish interaction between the virtual and real worlds.

The digital twin is gaining popularity faster due to a list of unique benefits that this emerging technology provides. For example, it can work from any place, generate real-time data, analyze and provide a clear report of the state of a machine, aiding decision-makers.

For example, the largest agricultural machinery manufacturer, Stara, has replaced its traditional production processes with Digital Twins to increase production efficiency and customer experience.

Google Maps have changed rapidly using the Digital Twin of the natural world using a massive amount of time-based data from a specific location of the world. The Digital Twinning of Google Maps shows us the geographic location and provides helpful directions to find the way to our destination.  

Digital Twin is one of the emerging technologies of the future. Furthermore, AI, IoT, and massive data have shaped the Digital Twin into powerful technology. Yet, most industries haven't adopted Digital Twin. However, the scenario is changing faster after the Covid-19 pandemic shock.

The Impact of Digital Twins in industries:

Catapult, a wearable technology company, has surveyed engineers to deduce the value that companies can derive by using Digital Twin technology at different stages of the lifecycle.

We must review these stats to see the big picture and understand the impact of Digital Twins in various industries. According to the Catapult survey:

What is Digital Twin, and why is it essential for businesses?

Benefits of Digital Twins Technology  in Business:

The benefits of digital twins are different for different industrial uses. However, the most common benefits of Digital Twins  include:

Read more: The Future Digital Twin: What Role Will Digital Twin Play in the Next Ten Years?

Digital Twin Applications Use Cases in a Few Industries:

Digital Twin applications are suitable for a wide variety of industries. Here we've just documented a few digital twin use cases below.

Digital Twins in the Automotive Industry:

Digital twins technology in the automotive industry has brought a massive revolution. Automobile companies are developing cars primarily in the virtual environment. Undoubtedly, it's fascinating.

Automobile companies plan the entire manufacturing process in the virtual environment using the Digital twin of production. This type of digital twin helps to determine how all compartments of the car will come together.

A digital twin of production also helps test and optimize new production lines to reduce time, workload, and risk for developing the physical car.

On the other hand, the digital twin of performance has significantly improved quality management and data analytics for automobile production. 

The Digital Twin of performance generates new insights about the production line by following a step-by-step process. First, the shop floor will feed essential data in the cloud system. The cloud system will then analyze the data to help optimize every stage of the production.

Digital Twin  in Healthcare:

The digital transformation of the healthcare industry is breathtaking as well. For example, the use of the Digital Twin technology in healthcare has helped to develop digital twins of organs and other anatomical structures, personalizing the medical devices to meet the individual needs of patients.

For instance, Dassault Systèmes SE, a French software company, developed a Digital Twin heart using MRI images and ECG measurements. This digital twin heart replicates the structure and some functions of the human heart. Now, heart surgeons can feed the patient data into the Digital Twin heart to determine whether the surgery will be successful.

Dassault Systèmes SE has launched the Living Heart Project in collaboration with academic and industrial members like Medtronic, Philips, and Boston. All the Living Heart Project members are working together to build safer and effective cardiac devices for patients.

The Digital Twin is no longer a hypothesis in the healthcare sector as it's already in use and expanding to make procedures of organ donation and surgery safer.

Digital Twin in Airline Industry:

Digital Twin in the airline industry is helping both the airline companies and jet engine producers to make critical decisions faster. In other words, digital twins are making it easier for them to analyze an extensive fleet of engines at a time. As a result, they can monitor risks and optimize operations to ensure safety, and develop new services that can be valuable to the customers.

The jet engine is typically dismantled every 20 to 24 months to examine the parts and repair if necessary.  Today, the Digital twin technology in the airline industry collects and analyzes about 2,000 critical characteristics of the jet engine to measure its performance. The digital twin also predicts the timing of the aircraft maintenance inspection.

In this way, the airlines can avoid significant disruptions in their daily flight schedules. They can provide the services as promised to their customers.

What is Digital Twin, and why is it essential for businesses?

How do companies use Digital Twins?

Companies use Digital Twins in different ways at different times. So, we can say that there are three types of Digital Twins based on the timing of the use:

Digital Twin Prototype (DTP)

Manufacturers start working on the product at The DTP. At this stage, manufacturers design, analyze, and plan out the process to predict the future shape of the actual product.

Digital Twin Instance (DTI)

The companies manufacture the physical product and build DTI. In other words, DTI is the twin of a physical asset. Developers will use DTI to run multiple tests and determine how the product will behave in different scenarios.

The DTI stays connected with the physical asset throughout its lifecycle. As a result, developers will add more operational data to improve it over time.

Digital Twin Aggregate (DTA)

The DTA is the aggregation of DTIs. Companies use DTA to cross-examine the physical product, predictions, and learning based on the collected data from the previous phase.

As you can see, companies use three types of Digital Twins for product development and re-designing, quality control and management, etc.

Read more: Why Accenture Lists 'Digital Twins' in Top-Five Technology Trends in 2021

How does a digital twin work?

The Digital Twin technology must have the ability to simulate and capture the undergoing events of the actual product to gather valuable insights on performance and future problems. So, the developers make sure that the Digital Twin is constantly receiving feedback data through sensors from the authentic product.

Components of Digital Twin are connected to a cloud-based system to analyze all the data received from the sensors against the existing business or contextual data. The data analysis in the cloud-based system helps to unfold new opportunities within the virtual model. Finally, developers apply these opportunities and scope to the actual product.

Digital Twin can also help determine the tests the manufacturers should run more often to improve the product.

Digital Twin is often developed alongside the actual product as a prototype to get feedback at any particular stage of its development. Sometimes the Digital Twin will be built as a prototype before the actual product comes into existence to determine future performances or failures.

Digital Twin can be simple or complex as you wish it to be. How accurately the Digital Twin will replicate the physical object will depend on the amount of data you are feeding into the Digital Twin.

Conclusion:

As we have mentioned above, that Digital Twin technology is not a hypothesis in the industries anymore. It's the new reality that's already in use, and manufacturers are benefiting from it.

According to Gartner reports, 13% of IoT-based companies are using digital twins already. In addition, 62% of the companies aware of Digital Twin are either establishing Digital Twin or planning to in the future. The Gartner report also claimed that 50% of the large industries would use Digital Twin Technology in 2021. Thus, they will achieve a 10% improvement in production efficiency.

With the rise of the popularity of emerging technology, companies are deploying AI, machine learning, software analytics, and cloud connectivity to empower the Digital Twin.

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