Digital Twin and Digital Transformation: Driving Business Growth with Advanced Technology
A Digital twin is a Digital Transformation of something in the same physical world. It may be physical (a device, system, product, or another asset) or conceptual (a service, process, or notion). The Internet of Things (IoT) makes it possible to create digital twins. Sensors that collect data from the physical world & send it to machines to reconstruct. So, It 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. Further, We can learn lessons from the digital twin that can be applied to the original system. It will include much less risk as well as a lot more return on investment.
The concept and practice of digitization in VUCA have become familiar to us all. Books have transformed into e-books, paper information is now in electronic formats, and digital processes have taken over. Music exists in bits and bytes, and the examples are endless. The term “digital twin” gained prominence in 2002 when Michael Grieves at the University of Michigan introduced it. Thanks to IoT technology, it has become more affordable as well as accessible to numerous businesses.
Digital twins are virtual representations of physical systems, processes, or products. Furthermore, They provide organizations with the ability to simulate, analyze, and optimize their operations. While digital twins offer several advantages, such as increased productivity, improved operational efficiency, and cost reduction, they also present certain challenges that organizations need to address in order to fully capitalize on their potential.
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Challenges during Digital Twin
The complexity of the data involved in creating a digital twin is significant. It encompasses a vast amount of information, including CAD models, sensor data, and historical performance data. Effectively managing and analyzing this data poses a major challenge for organizations. To make sense of it, they must invest in advanced data analytics tools and platforms.
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. To safeguard this data against cyberattacks and other security threats, the organization must establish robust security protocols and deploy effective monitoring systems. These measures are crucial for detecting and responding to potential security breaches in a timely manner.
The 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. The organization needs to equip its teams to leverage the full potential of digital twins.
Historically, industries have been using digital twins for their equipment such as machines and engines. 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 25 billion global sensors will be connected by 2021. A human heart, a jet engine, or 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 digital twin technology is to let us see what might happen if we were to make particular adjustments in real life. So, You can experiment with these adjustments on the digital twin without having to test possibly expensive changes on the real-world counterpart. Analysts Markets and Markets indicate that the digital twin market is expected to grow to $35.8 billion by 2025. Furthermore, 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 was collected from this network. Engineers use the digital twins as replicated models to 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 regarding their interactions with the landscape and wind, organizations can construct a digital twin for each wind farm in a computer. Subsequently, organizations leverage this digital twin to design an optimal turbine and engage in continuous refinement of the entire system. Once the wind turbine is installed, the digital twin model possesses the capability to gather and assess data from the physical counterpart. This invaluable process enables it to provide insights on how to further enhance the turbine’s efficiency.
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. Doctors use medical monitoring technology to collect data such as heart rate, oxygen levels, etc. Although the idea of a full digital patient is still off, they are already applying digital twin technology to one particular part of the body and seeing 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 also.
4. Financial Services:
Digital twin technology can easily observe customer behavior. In addition to this, 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.
The hospitality industry could make use of digital twin technology in the future to imitate real-life events and situations. For instance, CKE Restaurants Holdings has embraced digital twin technology to enhance productivity in its Carl’s Jr and Hardee’s restaurants. By digitizing restaurant floors and kitchens, the company gains the ability to experiment with different configurations. This enables them to reduce employee congestion and create a more favorable 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 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? So, This technology helps city planners understand & improve factors like energy consumption. There’s already digital technology of Singapore. In India, cities like Andhra Pradesh & Karnataka will create digital twin cities to fight against coronavirus.
8. Manufacturing Industry:
Companies can execute this concept with the IIoT (Industrial Internet of Things) in the manufacturing domain. They can design and deploy it in various ways, such as in tracking and monitoring systems, troubleshooting equipment usage, and evaluating production.
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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 this technology in every car. Through sensors, the physical car consistently sends data. 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. Engineers and designers also gain an understanding of what software updates cannot improve. This information is crucial in making significant innovation strides when developing 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–
Industries can consistently be reminded about production, operation, and management activities by using digital twins as a platform. 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 of an aerosol drug intended to reach lung tumors. By differing parameters on the Digital 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, this 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 more applications, use cases, and industries expand the use of twins. We’ll integrate them with more technologies, such as augmented reality, to provide an endless experience, speech capabilities, AI capabilities, and more. With technologies that enable us to take advantage of digital twins, we can eliminate the need to go and 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.