Digitalization encompasses many different facets ranging from business process transformation to digital twins. Digital twins themselves are really nothing special, considering that they have been around for a long time – just think of all the social media platforms and the profiles they maintain. However, the notion of a digital twin is also an interesting concept for businesses and is attracting increasing attention in digitalization projects. That’s because the technologies used in this process provide new perspectives on real objects or existing processes.
How companies can benefit from this and what role insight engines are playing in this process is brought to light in our blog series.
What is a digital twin?
“A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is an encapsulated software object or model that mirrors a unique physical object, process, organization, person or other abstraction. Data from multiple digital twins can be aggregated for a composite view across a number of real-world entities, such as a power plant or a city, and their related processes.”
In other words: It’s the digital representation of a process, a person, or an object that actually exists in real life.
It is precisely this coupling – of the real world with the digital world – that now makes it possible to analyze existing data with the aim of understanding and detecting problems that occur, say in production machines, before they actually arise (predictive maintenance). Digital twins are also exceptionally well suited for experiments, because planned changes can be simulated digitally without jeopardizing operations. This enables us to gain valuable insights and to draw up practical recommendations for action.
Creating a digital twin requires a few different elements. In addition to the real object that we want to depict (a machine, facility, component, or similar) and the virtual representation space, this usually and primarily includes the data that has been collected on the environmental conditions. All this information forms the ideal basis for analyses.
Gaining insight from existing data with insight engines
Insight engines analyze, interpret, link, and extract the relevant facts from existing information. Based on well known technologies from the field of enterprise search, insight engines are capable of capturing and processing all the different data sources with all their structured and unstructured data – including its meaning. The user receives a so-called 360-degree view, which is a comprehensive overview of a specific topic. Based on this perspective of the relevant information, it is possible to make predictions, simulate scenarios, and model possible impact and consequences.
Digital twins are already being used in a broad range of applications. In our next blog post, you’ll learn more about digital twins and insight engines and how they can be used in the area of aircraft maintenance.