16 Smart And Effective Uses For Digital Twin Technology

A digital twin is precisely what its name suggests: A digital copy of a physical object or system—even a human being. It may be a simple concept, but the potential applications are anything but. Through the ongoing collection and exchange of data, a digital twin can simulate and even predict the behaviors and reactions of its physical twin in a variety of conditions, providing invaluable insights to industries ranging from manufacturing to healthcare.

Digital twin technology allows businesses and organizations to test products and processes, study and predict how real-world conditions can affect physical objects and beings, and make well-informed, big-impact decisions with minimized financial and human safety risks. Below, 16 members of Forbes Technology Council share some of the fascinating ways industries and organizations are leveraging digital twin technology.

1. Minimizing Manufacturing Waste

We at Cuby use digital twin technology to make sure we produce 1-to-1 kits of the parts needed in our prefab construction process. It’s been estimated that up to 40% of the solid waste in the U.S. is construction and demolition waste. Manufacturing all the parts in advance allows us to reduce waste by up to 90%. – Aleksandr Gampel, Cuby Technologies, Inc.

2. Building Resilient Supply Chains

Businesses are increasingly using digital twin technology to build resilient and responsive supply chains. The digitization of supply chain processes provides businesses the opportunity to increase organizational efficiency by predicting serious problems and deceleration. In fact, it is estimated that by 2025, 80% of participants in industry ecosystems will rely on digital twin technology. – Radhika Krishnan, Hitachi Vantara

3. Mitigating Disruptions Due To Weather And Climate

Businesses are using digital twin technology to mitigate climate-related disruption. By combining data from public sources, such as weather data, with data from suppliers and partners, leaders can see how an unplanned weather event might impact the flow of goods across their supply chain, then use this insight to quickly pivot orders, routes or suppliers to limit waste and meet demand. – Rohit Shrivastava, Anaplan

4. Studying And Refining Processes

Process mining combined with simulation gives reliable visibility into as-executed processes (versus relying on what somebody thinks is happening) and the ability to do “what-if” analyses. This is effective because it allows one to see what’s really happening and simulate changes before making them. Often, changes do nothing or create a bigger problem elsewhere. Simulation and mining prevent that. – Michael Nyman, iGrafx

5. Making Data-Driven Manufacturing Decisions

The utilization of digital twins in the manufacturing industry has seen large growth. Digital twins increase productivity and reduce costs by combining the physical and digital worlds to make data-driven decisions, prolong asset life cycles and minimize unexpected maintenance disruption across assets. This modernizes the sector by moving from the “break and fix” approach to proactive maintenance. – Cindy Jaudon, IFS

6. Testing Health Intervention And Engagement Strategies

Health outcomes improve when patients are confident, connected and engaged. Digital twin technologies provide healthcare organizations the option to test drive new interventions and engagement strategies. This lowers the risks of rolling out new programs by testing hypotheses through a simulated pilot while also enabling cost-conscious innovation. – Trisha Swift, PricewaterhouseCoopers

7. Improving Patient Outcomes

A digital twin enables accurate and continuous monitoring. That data flow can inform data-driven decisions. For example, doctors are using an individual’s genetic makeup to model new organs for transplant. Because these processes can leverage a populationwide data set of digital twins, they can replicate an individual human body’s internal system to improve treatment outcomes for all. – Nicholas Domnisch, EES Health

8. Expanding Professional Services Capabilities

Knowledge-rich professional services firms are building digital twins of accountants, advisors and auditors using graph-based intelligent automation. These are distinct from previous technologies, because the decisions these professionals make are complex, contextual and nonlinear. In a world where there are big skills shortages and raging inflation, this form of IA is closing the gap. – James Duez, Rainbird Technologies

9. Onboarding And Knowledge Sharing

A digital twin use case that is an easy entry point and can provide quick ROI is training or onboarding. In areas where experienced employees are preparing for retirement, where there is high turnover or where there are general labor shortages, having a prerecorded “virtual” expert that can walk you through the instructions in real time can be a game changer and is much more effective than a giant paper manual. – Samantha Williams, Sonoco

10. Providing Safe Training

Today, manufacturing organizations are leveraging digital twin technologies to replicate machinery that would typically put employees in harm’s way. Here, a virtualized version of the original piece of machinery can be used to give employees training experience with the virtual machinery without also putting the employee’s health and safety in peril. – Marc Fischer, Dogtown Media LLC

11. Understanding Multidimensional Problems

Digital twin technology shines the brightest when it helps companies better understand a multidimensional problem—one that is too complex to easily solve. Because it is a way to visualize and make better decisions, the technology has become extremely effective for everything from product design to diagnosing medical issues to better understanding variables that affect business expenses. – Josh Dunham, Reveel

12. Improving Manufacturing Efficiencies

A very interesting field of application is manufacturing. Thanks to a digital twin of a production plant, with all its different lines and machines, we can launch simulations to generate greater efficiency or to detect potential bottlenecks. Simulating the manufacture of new products or variants of existing products is also a very useful application. – Miguel Llorca, Torrent Group

13. Developing And Training Self-Driving Vehicles

Without digital twin technology, it would be impossible to develop self-driving vehicles at the scale and with the reliability we are witnessing nowadays. Billions of simulations on a “virtual road” by a “virtual car” allow for training machine learning models to forecast accidents and plan not just the fastest, but also the safest, routes so that drivers can entrust the actual driving to robots. – Aleks Farseev, SoMin.ai

14. Budgeting And Financial Planning

Financial and operational data is the lifeblood of a company, but it’s difficult to “see all of it” and understand it in real time. Digital twins offer real-time, big-data-enabled simulation modeling that can be particularly useful for budget and financial planning. The technology can streamline tasks such as procurement, case management and capital resiliency and deliver powerful insights for finance leaders. – Nicola Morini Bianzino, EY

15. Managing Traffic

Digital twins are already effectively used by urban planning councils in many U.S. cities for efficient traffic management. They help in simulating real-world congestion at junctions, predicting what may get worse when and where, and they can be used to test multiple mitigation techniques by leveraging the best mix of ML and city know-how. Dashcam-backed digital twins are explored alongside junction twins. – Pramod Konandur Prabhakar, Pelatro PLC

16. Simulating Real-World Conditions

One way businesses are leveraging digital twin technology is by using it to simulate the physical world. For example, a company can use a digital twin to simulate a real-life situation so that they can predict how their product or service will behave in that environment. Another way is by using it to understand how their customers use their services and products. – Leon Gordon, Pomerol Partners

Successful CIOs, CTOs & executives from Forbes Technology Council offer firsthand insights on tech & business.

Source: Council Post: 16 Smart And Effective Uses For Digital Twin Technology

Critics By Carlos Miskinis Digital twin research expert

To explain what Digital Twin means in simple words, it is a digital replica or a representation of a physical object (e.g. aircraft engine, person, vehicle) or an intangible system (e.g. marketing funnel, fulfillment process) that can be examined, altered and tested without interacting with it in the real world and avoiding negative consequences.

Think of it as an online platform for testing, creating and altering objects that are based in reality, without engaging with them in the real world itself. Technologies similar to this one have been used in various industries long before this concept was created, however, this new definition of the technology has much more potential, power, and scalability that can replicate, monitor and test virtually anything you can think of.

The rise of the Internet of Things (IoT) has complimented the adoption of this new technology, as IoT has resulted in its cost-effective implementation. Virtual twins have become imperative to business today, consistently named as a strategic technology trend in recent years. The complexity of technology has led to many questions within the industry. One of the most important ones is how is it changing the way design, planning, manufacturing, operation, simulation, and forecasting is traditionally functioning?

A physical twin that was replicated on a virtual platform is a near real-time digitized copy of a physical object. It is a bridge between the digital world and the physical world. Its core use is to optimize business performance, through the analysis of data and the monitoring of systems to prevent issues before they occur and prevent downtime. The simulations that are produced will help to develop and plan future opportunities and updates within the process or product.

 The benefits of virtual twin technology are astronomical, with industries such as agriculture, government, transportation and retail experiencing rewards from the technology and benefits going forward. Companies must find methods to prevent the risk of potential product defects among their assets and future products. This piece of tech allows production costs to be minimized, as companies will save expenses when products are right the first time.

There is no need for expensive physical tests or updates to the products or process. Research with manufacturers has found that this concept will enable the reduction of development costs of the next generation of machines by well over 50%. The features of the tech also provide added confidence to boost product performance and aid complex decisions, preventing costly downtime to robotics and machinery.

The core benefit of why most companies started twinning their processes, products, and services via simulations is due to their efficiency. Businesses are racing to market their product faster than their competition, and having the ability to virtually simulate scenarios where a product is tested for failure via multiple angles helps the situation immensely. Not mentioning the fact that the development and testing costs are usually reduced hundreds of times.

This technology will be able to anticipate how the product and process will perform through digital simulations and analysis. The accessibility of reliable and consistently updated information provides the assurance needed to make faster decisions and increase the speed of production to overtake competitors. Here is a use case infographic we have presented in our workshop about understanding virtual twins – find event information here.

We can see how a virtual twin simulation is used to replicate and optimize machinery that regulates water flow in a factory. By doing this, developers can see every moving detail on the screen and then make the calculated decision to upgrade, optimize or make positive changes accordingly. Offices that adopt this technology early will attract innovative and leading talent. Offices will be able to incorporate interactive features to improve employee satisfaction and productivity using data-driven simulations.

Employees who will use digital twin technology will be able to expand their engagement with online tools, such as interactive maps to locate colleagues on the floor, book meetings and complete tasks with more diligence and accuracyManagers will also be able to supervise remotely with the tool that will be similar to a 3D map that will be created using virtual online platforms that are based on simulations.

 It is evident that the digital twin concept will benefit many people within the supply chain. Combining this disruptive concept with IoT technology is an incredible opportunity for businesses to improve. Ultimately, it will also allow stakeholders to improve the overall efficiency and cost of their business, and improve many aspects of work for employees….

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A Critical Piece Of The Machine Economy: The People

Over the shoulder view of young Asian businesswoman using AI assistant on smartphone

70% of GDP growth in the global economy between now and 2030 will be driven by the machines, according to PwC. This is a near $7 trillion dollar contribution to U.S. GDP based around the combined production from artificial intelligence, machine learning, robotics, and embedded devices. This is the rise of a new machine economy.

For those not familiar with the machine economy, it’s where the smart, connected, autonomous, and economically independent machines or devices carry out the necessary activities of production, distribution, and operations with little or no human intervention. The development of this economy is how Industry 4.0 becomes a reality.

Visionary leaders will implement new technologies and combine them with capital investments in ways that help them grow, expand, diversify, and actually improve lives. These machine economy leaders will operate in a new intelligent systems world in thousands of companies that will drive new economic models globally.

Sounds good so far, but all of that autonomous machinery isn’t going to build and operate itself.

Not enough people to do the work

While most people would agree that manufacturing is an important part of our economy, they aren’t recommending their children pursue that line of work. It’s expected that 4.6 million manufacturing jobs created between now and 2028 will go unfilled. Key drivers for this change include the fact that 10,000 baby boomers retire every day without people to replace them.

The workforce is quickly losing the second-largest age group, and millennials (the largest group) have so far not been attracted to manufacturing jobs at large. Instead they tend to be drawn toward technology, engineering, finance. The underlying issue may be one of perception, as the future of manufacturing will in fact include a much higher degree of technology, engineering, and finance in order to function.

Different skills are needed

Manufacturing jobs are changing. The number of purely manual, repetitive tasks are shrinking as technology advances to handle those jobs with robots and automation. Fifty percent of manufacturers have already adopted some form of automation, and now they need people with critical thinking, programming, and digital skills. Tomorrow’s jobs have titles such as Digital Twin Engineer, Robot Teaming Coordinator, Drone Data Coordinator, Smart Scheduler, Factory Manager, Safety Supervisor, and so on.

The shifts in productivity are happening so quickly, humans can’t keep up with them

An unskilled position can be filled relatively quickly as the prerequisite qualifications are limited. It typically takes months to fill a skilled position, and in most cases much longer for an individual to develop the requisite skills before they even think to apply. One alternative is to lower requirements in terms of education, skill, and experience in order to get someone new in the position, but then companies have to absorb the entire expense of training them.

Meanwhile there is increased pressure to utilize existing people’s and teams’ times and skills as much as possible, which can lead to burnout. This is a tenuous cycle that needs to be fortified by making sure our workforce has the skills training they need, when and where they need it.

In order to thrive in the machine economy, we need to invest significantly in people as well as in infrastructure. Focusing purely on infrastructure might lead to short-term and maybe mid-term profits, but ultimately it is not sustainable, and everyone loses. One can’t simply say, “We couldn’t fill the positions,” while there are people who need work.

Level-up our workforce

The human capacity to learn is basically limitless when individuals are motivated and have access to something to learn. There are several ways to tap into that capacity. First, we need to capture the knowledge and experience of the employees we have, so that those relevant skills can be passed on to the next wave of workers. We also need to ensure relevant training is available for people at every level of the company so that new people get up to speed and tenured employees don’t get left behind.

While some technologies need to be learned on the job, there is a level of foundational skill to understand in the machine economy, in addition to the technical and vocational skills required within a given field. An investment in, and possibly partnerships with, local schools could be a wise move for many companies. Lastly, while college is a great path for many people, it’s not the only form of higher education. Investments in vocational training and apprenticeship programs will be critical for our society to thrive in the machine economy.

Just as workers need to rethink and develop new skills, employers need to rethink and develop new ways of nurturing and attracting talent. To fully realize the promise of the machine economy, it is incumbent upon us to ensure people have access to the training and the tools they need in order to not only be successful but thrive. After all, what’s the point of all this technology if it doesn’t make life better for everyone?

PRESIDENT AND CEO

With more than 25 years of experience driving digital innovation and growth at technology companies, Kevin Dallas is responsible for all aspects of the Wind River business globally. He joined Wind River from Microsoft, where he most recently served as the corporate vice president for cloud and AI business development. At Microsoft, he led a team creating partnerships that enable the digital transformation of customers and partners across a range of industries including: connected/autonomous vehicles, industrial IoT, discrete manufacturing, retail, financial services, media and entertainment, and healthcare.

Prior to joining Microsoft in 1996, he held roles at NVIDIA Corporation and National Semiconductor (now Texas Instruments Inc.) in the U.S., Europe, and the Middle East in roles that included microprocessor design, systems engineering, product management, and end-to-end business leadership. He currently serves as a director on the board of Align Technology, Inc. He holds a B.S.c. degree in electrical and electronic engineering from Staffordshire University, Stoke-on-Trent, Staffordshire, England.

Source: A Critical Piece Of The Machine Economy: The People

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Critics:

Digital economy refers to an economy that is based on digital computing technologies, although we increasingly perceive this as conducting business through markets based on the internet and the World Wide Web. The digital economy is also referred to as the Internet Economy, New Economy, or Web Economy.

Increasingly, the digital economy is intertwined with the traditional economy, making a clear delineation harder. It results from billions of everyday online connections among people, businesses, devices, data, and processes. It is based on the interconnectedness of people, organizations, and machines that results from the Internet, mobile technology and the internet of things (IoT).

Digital economy is underpinned by the spread of Information and Communication Technologies (ICT) across all business sectors to enhance its productivity.Digital transformation of the economy is undermining conventional notions about how businesses are structured, how consumers obtain services, informations and goods and how states need to adapt to these new regulatory challenges.

Intensification of the global competition for human resources

Digital platforms rely on ‘deep learning‘ to scale up their algorithm’s capacity. The human-powered content labeling industry is constantly growing as companies seek to harness data for AI training. These practices have raised concerns concerning the low-income revenue and health-related issues of these independent workers. For instance, digital companies such as Facebook or YouTube use ‘content monitor’-contractors who work as outside monitors hired by a professional services company subcontractor- to monitor social media to remove any inappropriate content.

Thus, the job consists of watching and listening to disturbing posts that can be violent or sexual. In January 2020, through its subcontractor services society, Facebook and YouTube have asked the ‘content moderators’ to sign a PTSD (Posttraumatic Stress Disorder) disclosure after alleged cases of mental disorders witnessed on workers.

See also

References

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