What is a digital twin for? Use cases by industry
Blog: AuraQuantic Blog
In a previous article we explained what digital twins are, so to cover the topic in greater depth, in this article we will explore what a digital twin is for and some use cases for different industries, to better define and explain the value it can bring to a business.
What is a digital twin for?
According to Gartner analysts Marc Kerremans and Joanne Kopcho, “A digital twin of an organization is a dynamic software model of any organization that relies on operational and/or other data to understand how an organization operationalizes its business model, connects with its current state, responds to changes, deploys resources and delivers expected customer value.”
Use cases by industries
For a better understanding of why a digital twin is used, we are going to discuss some use cases segmented by industry. Of course, there are a multitude of possible use cases, and one factor to consider is whether we want to create a digital twin of the entire organization, or of only a part of it.
Use cases in healthcare
A good example may be that of a clinic that has its equipment connected to sensors. Data from these sensors, sent in real time, can notify of equipment failures immediately and arrange for maintenance teams to perform the necessary actions to prevent catastrophic failures. It is important to highlight that each piece of the connected equipment would have a virtual replica, empowering maintenance customization and optimizing the organization’s resources. Being able to store all that information, including the processes triggered for maintenance and their realization, will help to design the clinic and improve the acquisition, maintenance of equipment as well as extending its useful life. In addition, it is important to be able to incorporate some type of statistical simulation to improve the organization. With this system, a digital twin can be a valuable tool for improving the clinic and the service it provides.
Use cases in manufacturing
In the manufacturing sector, a digital twin can help to design new products, such as new machinery. In the design phase, engineers can replicate their behavior in different situations using 2D or 3D design. If, in addition, we add the data from the business regarding how the machine is used, manufactured and sold, we will improve the development of the new product. Once the product has been designed, the digital twin will continue to provide value by controlling the life of the new machine and using IoT, can provide information on its actual use and performance. A similar use case would be that of cars, in which 80 or 90 percent of the major decisions are made in the conceptual design phase of the car. With this type of activity, manufacturing companies accelerate their time-to-market and boost innovation.
Use cases in insurance and finance
If instead of talking about a physical product, we talk about a product such as insurance, or a financial product, replicating the conditions of sale and usage can help to generate better products and business lines which are more in tune with market demands. In this case, technologies such as statistical simulation, artificial intelligence, and Machine Learning etc., can help us analyze and make intelligent decisions, contrasted with historical business data to empower the design of better products that improve the user experience as well as the usability and adoption of these new products, and even help design new lines of business.
Summary
In each of the previous cases different technologies are used, depending on the industry and its particularities, but in all cases, some form of automation and intelligent analysis of business processes is necessary. This is where a low-code platform like AuraPortal can help implement a digital Twin.
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