Technology is touching new bounds and has reached a new edge, especially in the manufacturing sector. We live in the advanced era, where you can 3D print models at home, your desired products, and much more. The talks about a new technology called Digital Twins keep designers at the edge of their seats, with so many more possibilities and innovations awaiting. Something like this was much needed in the industry. In fact, according to Markntel Advisors study, “Global Digital Twin Market Research Report: Forecast (2022-2027)”, there is mounting demand for asset monitoring and improvement in workflow across different stages of a product’s lifecycle, including design, engineering, maintenance, and sales, which all calls for Digital twins, as it helps create predictive models to identify the possibility of success of physical prototypes before they are actually built.
What is a Digital Twin?
A Digital Twin replicates a physical entity, which could be a product, process, person, or place. To understand how it works, think about all the possible factors affecting this one product; it could be heat, wind, temperature fluctuation, etc., now imagine a digital form of this product, a replica that is made to represent and showcase the functioning of the product, is as similar as it can be to the real and physical product. This replica is now treated with all the possible factors in digitalized form. Doing this would show designers, manufacturers, and others to what extent the product can endure and efficiently work in a natural environment. It helps find the minute problems or scope for improvement.
This is the concept of Digital Twin. It uses real-world information using its data analytics, machine learning, and multi-physics simulation capabilities to predict the performance characteristics of its physical companions. Sensors installed on objects or assets demonstrate their real-time performance, operating scenarios, & changes over time, which ensure accurate modeling over a product’s entire lifetime.
What Is So New About Digital Twin?
With technology and so much advancement within the last decade, one may feel that new thing is undiscovered. However, though we are at the prime of technological advances, there is still so much more to discover and invent. Similarly, Digital Twin is the replica of a product in the real world. It allows and provides us to see the features, internal working, and status of the product in real-time, digitally, or through running numerous factors affecting the replica.
How Are Digital Twin and Simulation Different?
You must be aware of simulation and how it is often used to check if the product would be able to withstand a particular condition or factor. Basically, they are digital models which use computer-aided engineering (CAE) and computer-aided designing (CAD) and work by introducing different variables to the model to learn its effects and outcomes.
There are numerous key differences that we can focus on to understand what’s so new about digital twins and how they differ from simulations. The first is that the digital twin studies several stimulations after implementing real-time data and studies to overall effects. It focuses on the relationship between the product and the other elements and studies the two-way flow of information. In stimulation, different parameters and elements are introduced and tested to learn the working, reaction, and more information of the product. Here the product would develop and upgrade with the interference of an engineer or designer. Whereas a twin can upgrade through its lifecycle with the introduction of real-time data, offering integral, different insights and developments, which is not possible with stimulation.
In simpler words, Stimulation is the replication of what could possibly happen, while twin represents what is happening to the product in the real world. Digital twins, for instance, could predict when the product would lose its efficiency and because of what factors, whereas, in stimulation, this data would be entered manually as one of the possibilities. In the end, stimulation test different scenarios against set parameters, helping in product designing, while digital twin represents all the stages of the product lifecycle, much more than designing, and helps improve several processes.
Still at its developmental stage, the technology promises lucrative upliftment of several sectors, including manufacturing, healthcare, and automotive, eliminating the need for physical prototypes, minimizing production time, & enhances the quality of the final product or process. The added advantage of running several simulations and predicting the lifecycle and real-time issues in the product would provide the engineers with an upper hand in resolving such issues. In healthcare, in patient care and treatment would touch new heights with faster recognition of complications and other reflections of a patient’s ability depending on different variables. The technology is here to stay and upgrade the industrial sector tremendously while lightly touching and impacting many other sectors.