What is Digital Twin technology?

Digital twin is a digital representation of a physical object, process, or service. A digital twin could be a digital replica of a physical object, such as a jet engine or wind farms, or even much larger objects, such as buildings or whole cities. Alongside physical assets, digital twin can also be utilised to replicate processes to analyse and predict how they will perform under different conditions and can determine and monitor lifecycles.

Digital twins are created to allow a virtual computer model to collect feedback from sensors that collect data from the real-world version. This allows the digital version to imitate and simulate the operations of the original version. This is achieved by creating an interface between the digital model and an actual physical object to send and receive feedback and data in real time.

Why use it?

  • Streamlined design
  • Cost cutting
  • Reduced time to market
  • Predictive measures
  • Improved customer experience

A digital twin can be used to save time and money whenever a product or process needs to be tested, whether in design, implementation, monitoring, or improvement.

Digital twins can significantly improve enterprises’ data-driven decision-making processes. They are linked to their real-world equivalents and businesses use digital twins to understand the state of the physical asset, respond to changes, improve operations, and add value to the systems.

Types of Digital Twin

Digital Twin can be separated into four types:

Digital twin can also be broken down into three categories relating to the stage at which they are used:
* Digital Twin Prototype (DPT) - This is undertaken before a physical product is created * Digital Twin Instance (DTI) - This is done once a product is manufactured in order to run tests on different usage scenarios * Digital Twin Aggregate (DTA) - This gathers DTI information to determine the capabilities of a product, run prognostics and test operating parameters

Advantages and Diadvantages of Digital Twin

Advantages of Digital Twin

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Disadvantages of Digital Twin

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Improvements of Digital Twin

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Applications of Digital Twin

Real-life examples of digital twin

Digital twin technological impact on industries

The Future of Digital Twin Technology

“First we build the tools, then they build us.” ~ Marshall McLuhan

At present, engineering processes and machinery are so complex in design that experimenting with different approaches poses a risk of failure or disruption to the company that is too costly in finance and time for the company to afford. Implementation of digital twinning in companies enables teams to analyse the performance of business processes or products under different conditions. With successful deployment, digital twins have the potential to drastically innovate organisations’ development processes, saving significant money and elevating efficiency.

Potential applications of Digital Twin

Sustainability

(Accenture and Dassault Systèmes, 2021) in their work of Designing Disruption: The Critical Role of Virtual Twins in Accelerating Sustainability, explore use cases from five industries: construction and cities, consumer packaged goods, transportation and mobility, life sciences and electrical and electronics in advancing the understanding of how virtual twins could help meet the world’s sustainability goals. The application of digital twinning to these five industries alone can is predicted to unlock more than 7.5Gt of C02e emissions reductions through 2030 and US$1.3 trillion of economic value.

1. Construction and Cities  
Approximately a third of global green house gas (GHG) emissions are the result of commercial and residential buildings, accounting for 40 percent of global energy demand, 60% of the world’s electricity, and 25 percent of global water usage (Environmental Protection Agency, 2022). By integration of digital twin technologies within the broader framework of smart cities, consumption in buildings has the potential to be reduced by 30 to 80 percent.

2. Consumer Packaged Goods  
The consumer-packaged goods (CPG) industry currently accounts for two-thirds of international trade; agriculture, forestry and land use are responsible for almost a 25 percent of global GHG emissions and a staggering third of global food production is wasted across the value chain. With application of digital twins within the CPG industry, sustainable objectives can be applied at the start of the project lifecycle. Virtual prototyping allows for more cost effective testing in design alterations of consumer-package goods and manufacturing process driving significant CO2 benefits.

3. Transporation and Mobility  
Transport emissions account for 25 percent of global CO2 emissions in 2016 (Environmental Protection Agency, 2022) with this figure projected to drastically grow over time, challenging the decarbonization of the global economy. Research indicates zero-emission and autonomous vehicles to be key in achieving GHG reduction targets; digital twins allow manufacturers to test multiple designs and features in determination of design measures against policies and regulations. Furthermore, digital twins allow faster development of these zero-emission and autonomous vehicles that are so significant in our goal to reduce the global carbon footprint.

4. Life Sciences  
Life sciences are becoming increasingly pivotal in achieving our global goals of sustainability, however the industry itself is experiencing an increase in GHG emissions despite efforts of decarbonization as a result of increasing drug demand with the sector being approximately 55 percent more emissions intensive than the automotive industry.

Application of digital twin to this sector will allow scientists and researchers to digitalise the production process in running multiple scenarios with the objective of finding optimal configuration, speed acceleration and accuracy while reducing waste, including emissions.

5. Electrical and Electronics  
The electrical and electronics industry faces serious sustainability challenges; the manufacturing of equipment alone generates over a third of associated CO2e life cycle emissions. Successful deployment of digital twins can enable designers to follow circular economy principles throughout design and guide waste management in tackling the problem of e-wastage.

Pharmaceuticals

The deployment of digital twins in the pharmaceutical industry is still rudimentary, however data scientists have the vision to develop a high-yielding and versatile pharmaceutical manufacturing sector by adopting digital twin concepts and applying them to drug research and development, pharmaceutical supply chain management, and other manufacturing practices.

  • Unlearn.AI recently received $50USD million Series B funding to advance the use of patient digital twins in clinical trials within cell therapy, where a patient’s modified cells are used for treatment. In this case, the information extracted from a patient is digitally collated and then channelled safely to the production equipment for analysis. For example, gene analysis is carried out to produce a personalized drug for the patient.
  • In October 2021 (TwinHealth, 2021) secured a $140USD million Series C Funding to scale its ‘Whole Body Digital Twin’ service for chronic metabolic disease. Its Whole Body Digital Twin is a predictive digital tool, created using patient digital twins, to provide personalised nutrition, sleep and medicine through an application.
  • The EU-funded Neurotwin Project (Neurotwin, 2021) aims to incorporate digital twins for developing personalised hybrid brain models in treatment of conditions such as epilepsy and Alzheimer’s of which recent findings suggest non-invasive electrical brain stimulation to be a potential treatment. It is the objective of the project to employ the personalised brain models to design and test personalised neuromodulation protocols capable of restoring healthy dynamics with a predicted end date of 31 December 2024.

What’s next?

Collaborating Twins

Just as humans collaborate to innovate, so too will digital twins. A digital thread is responsible for much of the value associated with digital twins, this is the communication network that enables a connected flow of data and unifies diverse but interrelated datasets in order to uncover insight.

​(MITSloan Management Review, 2020) use the example of a car ride. If you want to get from point A to B; however, you are siloed from every other driver, if every driver knew where everyone else needed to get to, travel time would become shorter for everyone. Connecting the digital twins of cars enables a fully autonomous car grid and innovation in mobility systems.

Furthermore, linking digital twins of completely different types of assets can feed the digital twin of more complex entities. An entire city, for example, could connect information from digital twins tied to weather patterns, pollution, citizens, traffic, transforming smart cities to conscious cities that are aware of assets flowing in and out of their borders.

Corporate Innovation

Similar to the promise of collaborating twins, the theory of corporate innovation pertains the idea that digital twins can connect all of an enterprise’s information, providing companies with a real-time holistic view of their operations, and allowing them to swiftly improve operating models, develop better strategies and discover new pockets of efficiency and, perhaps, finally eradicate silo mentality.

By adopting digital twins, companies can more effectively shift from the production and sale of a product to selling the use and maintenance of that product as a service. Consider Kaeser Kompressoren, a German company that used to sell air compressors. After introducing digital twins, it has moved toward selling air-as-a-service, where the customer only pays for their use of the compressor.

Multiplier Effect

The emergence and development of digital twins is coming at a time of particular scientific and technological development with many other new technologies finding their footing as well. Digital twins will combine with other emerging technologies to multiply their potential for innovation.