Addressing Your Challenges with Digital Twins

The market for digital twins is exploding. According to Gartner, in 2019 an estimated $1.2 billion will be invested in digital twin technology. By 2024 that same market is expected to grow to nearly $8.5 billion, an annual growth rate approaching 40%, with companies realizing gains of 10% thanks to optimized decision making. A broad cross-section of industries have begun to embrace these software tools to optimise processes, make better decisions, and choose the best strategies for everything from maintenance to manufacturing. 

Yet at the same time there isn’t always a lot of clarity about what a digital twin actually is. Some see digital twins as a natural successor to the Internet of Things (IoT), a “logical progression” from the monitoring sensors that have become ubiquitous in industry. Others talk about digital twins as a bridge between the physical and the virtual world and a chance to realise benefits “for built asset all across the globe”. Less enthusiastically, some see digital twins in industry as the first step towards a dystopian world where digital twins of people diminish the moral value of a human life.

So what, then, should we make of digital twins: will they be transformative or destructive, are they merely an extension of work in the world of sensors or a truly transformative technology? 

In this series we’ll dive into the world of digital twins and explore the ways in which they are changing the way that decisions are made. In future installments we’ll look at the cost of deploying a digital twin, the business case for digital twins, the sorts of use cases that benefit most from digital twins, and how to scale a deployment of digital twins.

But let’s start with something more fundamental and define just what a digital twin is, the different types of digital twins, and why a company might want to be part of the global rush to adopt this technology.

Four Types of Digital Twins

Technology research and advisory firm Gartner defines a digital twin as “a software design pattern that represents a physical object with the objective of understanding the asset’s state, responding to changes, improving business operations and adding value”. 

In other words, a digital twin is a virtual representation of something in the real world that helps the software user to better understand what has happened, is happening, and will happen to that same real world object. However, while digital twins once only referred to representations of physical machines or assets, today the definition has shifted and broadened: a digital twin can now be a virtual representation of an individual asset, a connected workflow, a business organisation and management system, or an entire enterprise at all levels of granularity concurrently.

In a factory setting, for example, a digital twin of a machine could collect data, including real-time sensor data, about that machine and feed it into a software model of the machine. This model would help the factory manager to understand the stresses that their machine is under, determine the optimal point to schedule a maintenance intervention, and be warned about any potential performance issues before they arise.

This digital twin of a single entity is the most common and, according to Gartner, the world’s 20 billion connected sensors and endpoints have the potential to power billions of individual digital twins by 2021.

Digital twins, however, can be more complex than just a virtual representation of a single machine. To return to the factory setting, a second type of digital twin is one that connects multiple machines in a single workflow. For example, instead of an automotive manufacturing plant having individual digital twins of the two dozen robots in its final assembly line, the plant owners could invest in a digital twin of how those robots work together.

A digital twin of a workflow or process is understandingly more complex than a digital twin of an individual machine, asset, or object. However it also has the added capacity to help the user make decisions about any part of that process taking into account the impact of that choice on the process as a whole.

Some businesses, though, are taking their digital twins investments to the next level again, and investing in what are called digital twins of organisations, or DTOs. Gartner defines a DTO as:

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 exceptional customer value. 

This class of digital twins goes beyond virtual representations of a single machine or a factory workflow to encompass all of the systems and processes of a company that might impact on their operations. A DTO not only models and simulates the machines and processes on the factory floor but also the constraints on the factory - financial, regulatory, human resources, even environmental - to provide an accurate, reliable, and robust representation of reality.

Finally, there are advanced digital twins for industrial clients known as an enterprise digital twin. This is the next and obvious evolution in digital twin technology and combines iterations of the previous three digital twins into a single software solution. 

An enterprise digital twin offers users the opportunity to model and simulate individual assets as single entities, to optimize processes in a workflow, and also to extract strategic business value as a DTO does. These enterprise digital twins are what Cosmo Tech builds for clients in the automotive manufacturing sector, in the transport sector, the aerospace industry, and the utilities space. They allow for a truly holistic approach to decision making with a clear understanding of the impacts of any choice on the entire system, no matter whether that choice is made on a factory floor or the corporate boardroom.

Enterprise Digital Twins and Strategic Transformation

Gartner has identified digital twins as a strategic technology trend for 2019 and, with billions in investment flowing into the sector in the next five years, it’s a trend that looks set to continue. Companies can realize optimisations and savings quickly with single-asset digital twins, more complex, whole system digital twins of business process and workflows, or business-process focused DTOs. Those organizations that embrace enterprise digital twins, however, stand to realize the greatest gains as they lift productivity and realise gains not only in a single plant or asset class, but within and across the entire organisation.