Digital Twins – The Fortune Tellers

23

September

2022

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Digital Twins—what a fancy and classy name for a piece of software! In a nutshell, digital twins is software that utilizes real-world data in order to generate simulations that can forecast how a process or a product will perform or behave. This is accomplished by combining the Internet of Things, Artificial Intelligence, Augmented Reality, and software analytics to improve the output and correspondingly optimize the ways a company generates value.

However, what I just described isn’t the concept of simulation? The answer is no. Even while simulations and digital twins may share common elements by both utilizing digital models to imitate a system’s operations, a digital twin is fundamentally a virtual environment. In essence, we could liken digital twins to multitaskers. A simulation is typically associated with one particular process or perhaps a part of the process, while a digital twin may itself run multiple simulations simultaneously. But the core difference goes beyond the digital twin’s capacity for multitasking. The picture now includes real-time data. Digital twins are built on a two-way flow that commences when object sensors give the system processor pertinent data and continues when the processor shares insights with the original source object.

Digital twins are able to study problems from far more vantage points than standard simulations can because they have better and constantly updated data related to a wide range of fields, combined with the added computing power that comes with a virtual environment, which has a greater potential to improve products and processes in the long run.

To summarize the benefits, companies can use digital twins to avoid wasting significant budget resources and effort developing a product only to discover that it requires refinement. Digital twins appear to be like fortune tellers who can envision the future and advise on the best courses of action. Moreover, after a new product has gone into the production phase, digital twins can aid in controlling and duplicating production systems with the main objective of maintaining excellent performance throughout the manufacturing cycle. Furthermore, digital twins promote sustainability since product manufacturers can determine which product materials can be harvested once the product reaches the end of its lifecycle. Hence, the industries that operate on large-scale products or projects , such as engineering, health care, automobile manufacturing, aircraft production, and railcar design, benefit the most from digital twins. In addition, stakeholders can participate early in the development process and check and modify the Digital Twin as needed. Fewer prototypes, lower costs, and shorter lead times will be the results of the rapid development iterations that the digital twin permits.

In 2022, there will be many technology giant companies that have developed platforms that offer digital twin software in combination with real-time agent collaboration and many more features. Indicatively, Microsoft has developed the Azure Digital Twins platform as a service (PaaS) offering that enables the construction of knowledge graphs based on digital models of whole environments. These ecosystems might include whole cities as well as structures such as buildings, industries, farms, energy networks, trains, stadiums, and more. Oracle, IMB, Siemens, and General Electric are only a few other examples of companies that have developed their own digital twin platforms. 

Sources

azure.microsoft.com. (2022). Pricing – Digital Twins | Microsoft Azure. [online] Available at: https://azure.microsoft.com/en-us/pricing/details/digital-twins/ [Accessed 23 Sep. 2022].

www.ibm.com. (2021). IBM Digital Twin Exchange – Overview. [online] Available at: https://www.ibm.com/products/digital-twin-exchange [Accessed 23 Sep. 2022].

www.twi-global.com. (2022). What is Digital Twin Technology and How Does it Work? [online] Available at: https://www.twi-global.com/technical-knowledge/faqs/what-is-digital-twin [Accessed 22 Sep. 2022].

van Rijmenam, M. (2022). Why Digital Twins Are One of the Building Blocks of the Metaverse. The Digital Speaker. Available at: https://www.thedigitalspeaker.com/digital-twins-building-block-metaverse/ [Accessed 23 Sep. 2022].

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Taking Care of Virtual Patients

30

September

2018

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In engineering, the concept of ‘Digital Twins’ has gained attention during the last decade. A Digital Twin is a virtual representation of a physical object, which is continuously fed with data from embedded sensors and software. Hereby, the Digital Twin tightly connects the physical system with its computer model. Digital Twins are, for examples, widely used to continuously monitor and forecast the health of jet engines. This allows airlines to identify how and where potential problems could occur, whereby predictive maintenance is deployed to keep the system healthy.

In this blog, I will explain what the possibilities and corresponding benefits and risks are for this technology in the healthcare industry. The enhancement of computational power and molecular readout technologies has increased the potential of ‘virtual patients’ to continuously track health and lifestyle parameters. As of now, the digital models used in healthcare are quite partial (such as twin models of the heart) and basic. Yet, already signs of the effectiveness of these models can be observed as well as the benefits it could bring in the future.

First, the data-rich Digital Twins would allow for the creation of a more detailed picture of the patients which results in faster and more accurate identification of actual or potential disease states. Hereby, a shift to more preventive solutions could result in significant health improvement and hence reductions of health care costs. Second, the multidimensional properties of the digital twins could allow practitioners to more accurately compare a patient’s health with the health stats of similar patients. Since clustering can be based on more elements than, for example, age and gender, deviations from the ‘normal’ can be identified faster and more accurately.

Yet three main societal concerns are also worth noting. First of all, Digital Twins could raise inequality since developing a digital version of yourself could be very costly. Hence, the benefits of improved health and possible life extension could potentially only be accesses by wealthy people. Second, the Digital Twin could lead to self-fulfilling prophecy mechanisms where knowing that you could potentially become sick in the future will make you indeed feel sick and weak. Thirdly, it is of great importance to ensure data protection. Data leaks could quickly offset the potential benefits of Digital Twins, as for example, insurance companies could use the data to modify the insurance policies for individuals in their favor

The future will tell whether we will be able to effectively govern this emerging technology in the healthcare industry; thereby significant health and cost benefits can be obtained by actively managing the associated concerns.

 

 

 

Sources:

 

Bruynseels, K., Santoni de Sio, F., & van den Hoven, J. (2018). Digital twins in health care: Ethical implications of an emerging engineering paradigm. Frontiers in genetics, 9, 31.

 

Mussomeli, A. (2018). Expecting Digital Twins. Deloitte Insights. Retrieved from: https://www2.deloitte.com/insights/us/en/focus/signals-for-strategists/understanding-digital-twin-technology.html

 

Van Houten, H. (2018). The Rise of the Digital Twin: How Healthcare Can Benefit. Philips Research. Retrieved from:https://www.philips.com/a-w/research/blog/the-rise-of-the-digital-twin-how-healthcare-can-benefit.html

 

 

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