Digital Twins and Digital Transformation: Driving Business Growth with Advanced Technology
A digital twin is a digital replica of something in the physical world. It may be physical (a device, system, product, or another asset) or conceptual (a service, process, or notion). Digital twins are made possible due to Internet of Things (IoT) sensors that collect data from the physical world & send it to machines to reconstruct. Digital Twin is the virtual representation of a physical environment. With a digital twin, as the name indicates, we have two versions of a ‘thing’: the physical one & the digital twin one.
By generating a digital twin, perception about how to improve operations, increase efficiency or discover any problem are all possible before it occurs. The lessons learned from the digital twin can then be applied to the original system with much less risk & a lot more return on investment.
We all have grown used to the concept & practice of digitization in VUCA: books turned into e-books, paper information turned into electronic formats & digital processes, music in bits & bytes, the list goes on. The concept of a digital twin attained attention in 2002 when Michael Grieves at the University of Michigan first used the term, it was IoT technology that made it economical & attainable to many more businesses.
Digital twins are virtual representations of physical systems, processes, or products that enable organizations to simulate, analyze, and optimize their operations. While digital twins offer significant benefits, such as improved productivity, enhanced operational efficiency, and reduced costs, they also pose certain challenges that organizations must overcome to fully leverage their potential.
Also Read : 21 Best Digital Transformation Books
Challenges during Digital Twins
Complexity of the data involved – Creating a digital twin requires a massive amount of data, including CAD models, sensor data, and historical performance data. Managing and analyzing this data is a major challenge, and organizations need to invest in advanced data analytics tools and platforms to make sense of it.
Lack of standardization – There is currently no universal standard for digital twins, and different organizations may use different models and platforms. This can make it difficult to integrate different digital twins and share data across different platforms.
Security – Digital twins contain sensitive data, and organizations need to ensure that this data is protected against cyberattacks and other security threats. This requires implementing robust security protocols and monitoring systems to detect and respond to potential security breaches.
Challenge of cultural change – Creating and implementing digital twins often requires significant changes in organizational culture, processes, and workflows. Organizations need to invest in employee training and change management programs to ensure that their teams are equipped to leverage the full potential of digital twins.
Historically, digital twins have been used for industrial equipment (machines, engines, and the like), but the concept of a digital twin is also widely applicable to abstracting all the ways we live & work in our physical environment. Abstracting the composite interactions & high-value intersections between places, people, and things are exploring new opportunities, creating new efficiencies, and improving public & private spaces.
Gartner predicts that by 2021, there will be 25 billion connected global sensors. A human heart, a jet engine, even a whole city can all have a digital twin that reflects the same physical & biological properties as the real thing. You can think Digital twinning concept as a bridge between the physical & the digital worlds.
Embrace digital twin technology as a strategic tool for innovation, process optimization, and informed decision-making.
Practical Application of Digital Twin
Data scientists develop digital twins that can receive input from sensors that gather data from their real-world peers. The idea behind a digital twin technology is to let us see what might happen if we were to make particular adjustments in real life. These adjustments can be experimented on the digital twin without having to test possibly expensive changes on the real-world counterpart. Research by analysts’ markets and markets indicates that the digital twin market is expected to grow to $35.8 billion by 2025. The industries that grasp the benefits of digital twin technology are:
1. Automotive Industry:
The future of autonomous vehicles lies in well-connected road systems & vehicles. Evaluative data collected from this network. The digital twins then act as replicated models that help engineers evaluate the behavior of vehicles before they are used on roads during transformation.
2. The Energy Sector:
GE has used digital twin technology to create a Digital Wind Farm, a cloud-based model of a wind farm. By collecting data from the machines about how they interact with the landscape and the wind, they build a digital twin for each wind farm in a computer & then use it to design the productive turbine, & then keep adjusting the whole thing. Once the wind turbine is installed, the digital twin model can gather & evaluate data from the real-life version and suggest ways to make it even more efficient.
With digital twinning, it should be possible to create a “digital patient” – a digital model of a human body that shows some measurements of the body. Medical monitoring technology is used to collect data such as heart rate, oxygen levels, etc. The idea of a full digital patient is off yet, but digital twin technology is already being applied to one particular part of the body & showing great promise. Philips created a clinical application called Heart Model, which generates a personalized 3D view of a patient’s heart based on 2D ultrasound pictures. As Philips sees it, maybe one day a virtual heart could save your real one.
4. Financial Services:
Customer behavior can be easily observed with digital twin technology. It helps in making personalized profiles for individuals via data analysis of their previous behavior in buying decisions etc. It can also imitate cash flows & balance sheets.
Digital twin technology can be used to imitate real-life events & situations, and this could play a major role in the hospitality industry in the future. For instance, CKE Restaurants Holdings has been using digital twin technology to amplify productivity in its Carl’s Jr & Hardee’s restaurants. Restaurant floors and kitchens were digitized, permitting the company to test various configurations that would help to decrease employee traffic & improve the environment for customers.
6. Retail Environments:
The digital twin is rather a new concept in retail, but it can be worthy, especially when you need to design customer behavior in stores. Analytics company Pygmalios is spotlighting digital twin technology as part of Retail 4.0 – an approach that collects granular, real-time data from physical retail environments & uses that data to improve awareness of customer activity and behavior.
7. City Management:
If you can have a digital twin of a wind farm or restaurant, why not the whole city? Digital twin technology helps city planners understand & improve factors like energy consumption. There’s already a digital twin of Singapore. In India, cities like Andhra Pradesh & Karnataka will create digital twin cities to fight against coronavirus.
8. Manufacturing Industry:
The Digital Twin concept with the IIoT (Industrial Internet of Things) is executed in the manufacturing domain. It can be designed & deployed in various ways such as in tracking & monitoring systems, troubleshooting equipment used, evaluating production, etc.
Best Video for you-
Benefits of Digital Twin
1. Consistent Evaluation-
Now that sensors can capture & consistently update the product’s digital twin throughout its lifetime, manufacturers can look inside the product all the time.
For instance, Tesla uses a digital twin in every car. Through sensors, the physical car consistently sends data to its digital twin. If the vehicle has a shaking door, the system will remind you to download software that will adjust the door’s hydraulics.
As Tesla gathers information about the performance & use of each vehicle, its engineers also combine the data to create updates that will improve the performance of that particular range of cars, an actual example of real-time innovation. This process also helps engineers & designers understand what can’t be improved with software updates alone which is the important information to make bigger innovation jumps when planting the next version of a product.
2. Automated Perception-
An IoT-enabled environment needs to understand the relationship between several types of data within its network. This IoT data can be withdrawn & enhanced in the form of knowledge graphs. This helps in automating processes & improving decision-making during digital transformation.
3. Predict the Failures–
Digital twins provide a platform that enables industries to be reminded consistently about production, operation & management activities. The virtual testing platform that it provides, imitates real-world data into critical & meaningful perception. In addition to being a flexible solution, it also self-diagnoses problems. This makes it easy for industries to make human-machine interaction systematic & productive.
4. Faster & Cheaper Framework–
Digital twinning can decrease the requirement for expensive tests & physical prototypes, decreasing the cost & increasing the speed of innovation.
For instance, Oklahoma State University developed a digital twin of an aerosol drug intended to reach lung tumors. By differing parameters on the digital twin such as inhalation rate & particle size, scientists increased the no. of particles reaching their target from 20% to 90%, sparing them the need to create several prototypes and shortening the testing process.
5. Digitizing the Complete Industry Ecosystem-
There is a quick adoption rate of digitizing operations by industries regularly to attain positive business outcomes. This up-to-date & personalized data amplify productivity & profitability. In addition to being a high revenue opportunity, the digital twin technology also digitizes the working assets & processes in its totality.
Foster cross-functional collaboration to maximize the potential of digital twins, breaking silos and driving holistic digital transformation.
In the future, we’ll see twins expand to more applications, use cases & industries and get integrated with more technologies such as augmented reality for an endless experience, speech capabilities, AI capabilities, more technologies enabling us to take advantage of digital twin eliminating the need to go & check the ‘real’ thing and so on. The globe is yet to witness over 50 billion connected devices by the period of 2020-2030 & over 7 billion customers using the web worldwide.
Frequently Asked Questions
Are digital twins AI ?
Digital twins are not necessarily artificial intelligence (AI) in and of themselves, but they often use AI as a key component.
Why digital twin fails ?
Digital twins may fail due to a variety of reasons, such as incomplete or inaccurate data, inadequate computational resources, lack of standardization, and insufficient integration with physical systems. In addition, organizations may fail to fully leverage the capabilities of digital twins due to cultural resistance, insufficient training, or inadequate change management processes.
- Advanced twins offer real-time information and reenactments to upgrade operational proficiency, prescient upkeep, and product/service customization.
- Leveraging computerized twins engages organizations to move forward nimbleness, responsiveness, and by and large client encounter within the computerized period.
- Fruitful integration of computerized twins requires vigorous information administration, security measures, and adaptable foundation for maintainable execution.