More businesses are turning to digital twin technologies to improve their products, lower costs, and increase productivity. According to a Deloitte study, “digital twins” are expected to grow by up to 38% and reach a whopping $16 billion by 2023. In fact, major companies such as Amazon and Microsoft have already started offering services designed to make these technologies more accessible for businesses.
What are digital twin applications?
Digital twin technology applications allow people and businesses to make exact digital representations of products and processes. One major advantage companies are seeing from these is their ability to assist with the planning of large, complex projects.
For example, when it comes to applications of digital twin technology, construction firms can use them to analyze the performance of buildings and adjust as necessary to boost efficiency. This is made possible through snapshots that digital twins can provide of their physical counterparts. In turn, the snapshot data is transmitted to a remote, human operator who can see any suggestions being made by the twin. Suggestions are commonly issued when the digital twin detects a problem and wants to offer solutions or potential improvements to the human operator.
Educational institutions are seeing the benefits of these technologies as well. In fact, Fierce Education recently discussed Stanford University’s decision to incorporate digital twin technology in its education, construction, and engineering programs. What they concluded is that students tend to be more motivated and have an overall better learning experience when utilizing digital twins.
What makes digital twins more intriguing, however, is their ability to replicate entire processes. The prior-mentioned Deloitte study uses manufacturing plants as an example saying, “a manufacturing plant could be modeled so that a digital equal replicates each piece of equipment and element of the operation, allowing someone at a computer or console to simulate the entire manufacturing process and get accurate results.”
What challenges do digital twin applications solve?
Digital twin technology applications are ideal for engineers and product designers or anyone looking to potentially lower costs, optimize processes, and improve their customers’ journeys while maintaining a collaborative approach with team members.
Solutions for engineering and product design
Anyone looking to design a product could essentially benefit from the use of digital twins because they allow designers and engineers to view a product digitally before there is ever a physical, tangible object. This is obviously very cost-efficient for engineers because it allows them to locate any potential design flaws prior to the physical product being created.
Global Logic discusses the benefits for engineers saying, “this new capability improves risk assessment, accelerates the development of new products, and enhances the product line’s reliability”.
Lowering costs and optimizing processes
The opportunities are endless when it comes to lowering costs and streamlining processes. Because digital twins are, in part, built to detect the likelihood of unexpected outcomes, they are invaluable when it comes to lowering costs for businesses, particularly those that operate with costly machinery.
Imagine being able to detect potential flaws before a machine is ever physically turned on or even built, for that matter.
A more collaborative approach
Using applications for digital twin, teams can monitor progress 24/7 in real-time. This provides better collaboration efforts as members can essentially “tap in” any time they are seeking a status update.
Tracking progress and setbacks remotely
As mentioned, status updates are provided to teams remotely in real-time, allowing for optimal efficiency and productivity within the team. This was previously unattainable, with staff bound to a strict location while working on large systems.
Improving the customer experience
It’s no secret that a satisfying customer experience is one of the top goals for most companies. That’s why they spend lots of time analyzing data to ensure customers are offering positive feedback for their products.
Digital twins allow companies to quickly analyze performance and decide what adjustments should be made to their next product.
Examples of digital twin technology applications
Digital twins have the capacity to be used in various industries. From healthcare to manufacturing, digital twins have something to offer.
Digital twin applications in the fitness industry
Although applications for digital twin are still relatively new in the world of sports, they are becoming increasingly popular within the fitness arena, especially concerning fitness app development.
A 2020 study published by the University of Milan found that digital twins are a good tool for fitness trainers and athletes that are looking to optimize their performance.
The study involved using digital twins to track the behaviors of athletes. This included how much food they were eating and how much activity and sleep they got. Once enough data was collected, the digital twin was able to make predictions about the physical twin’s performance. If the predictions were less than ideal for the athlete, the digital twin makes suggestions for behavior changes.
The study also discussed using wearable SmartFit technology to support trainers and coaches, which works by using loT sensors to track things such as food income and mood. SmartFit takes these measurements on an ongoing basis. Ultimately, this information is used as dynamic data to keep track of the athlete’s vitals.
In the long run, these metrics are stored as historical data and utilized to make accurate predictions as to the athlete’s performance. Although this study focused specifically on sportspeople, this type of monitoring is easily adaptable and can be used in various industries.
Applications of the digital twin in manufacturing
Applications for digital twin have various uses within the manufacturing industry. Using high-cost equipment provides a great deal of risk for businesses in manufacturing. If a malfunction occurs, repair costs can be quite costly. In addition, large machines generally require a great deal of data in order to function. The creation of digital twins assists with both keeping these costs low and carrying large amounts of data to make accurate predictions.
As previously discussed, perhaps one of the most attractive features for engineers is the ability to make a digital copy of a product before a physical copy is ever produced, which allows them to anticipate any needed changes before constructing the physical version. Defective end products or ones demonstrating low performance can be addressed quickly and efficiently.
In addition, businesses can use applications for digital twin to construct multiple variations of a product so that it can be specifically tailored to each customer’s individual needs. Currently, digital twins are commonly used by manufacturers to predict downtimes of machines so they can lower maintenance times and subsequently improve productivity. Keep in mind that this is not always feasible due to the costly nature of data for predictive maintenance.
Read also: 10 use cases of AI in manufacturing
Applications of digital twin in the automotive industry
Applications for digital twin are especially beneficial for car manufacturers because the planning process that takes place to design a vehicle already heavily relies on technology.
The digital twin of a car makes up everything from its software to its mechanical behavior. Through simulation and analysis, many problems are already fixed before an automobile is ever physically built.
An article from Siemens discusses an example of physical behavior simulations for automobiles. The company uses 3D data to refine elements like material behavior, heat management, and the vehicle’s airflow. Other factors such as mechatronics, electronics, system-on-chip, and embedded software are simulated as well.
The article goes on to discuss the cost-efficient nature of these methods, pointing to a few factors. Firstly, the lower number of needed prototypes, and secondly, allowing staff from multiple departments to work on a common project simultaneously. This ability for real-time collaboration supports the introduction of new measures and processes, such as additive manufacturing.
Digital twin technology applications are beneficial for self-driving automobiles as well. Because self-driving cars rely heavily on sensors to maintain equilibrium within the vehicle itself as well as outside forces, digital twins are an optimal source for reducing liability. Liability is lowered because these applications test every aspect of the vehicle prior to any physical operation.
Digital twin applications in the healthcare sector
Perhaps one of the most challenging issues right now in healthcare is low staff-to-patient ratios, which greatly increases the risk of adverse events within hospitals. Not to mention, the added possibility of malpractice suits.
It has been reported that over the next three years, up to 66% of healthcare executives are looking to invest in digital twin technologies. A major part of these decisions comes in light of the COVID-19 pandemic and the vital role that digital twins have played in aiding healthcare workers.
The Digital Twin Consortium, which focuses on raising awareness for digital twin technologies, has observed their potential to improve wait times within healthcare settings, cut expenses, and, most importantly, reduce the number of bed shortages.
Additional options for health professionals include customized treatment plans, optimized surgical planning, testing medical devices and drugs, and addressing supply chain shortages.
Read also: Applications of AI in the energy sector
Applications of digital twin technologies
Applications for digital twin technologies can be of great assistance to IT specialists and data analysts to help optimize their processes and workflow.
They allow for predictable “what if” scenarios to be created that may otherwise be overlooked, simplifying the development process and potentially catching missing pieces.
As developers continue to design more advanced solutions, technology like the digital twin will help support software engineers and developers as solutions get more complex and intricate.
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