What Is Digital Twin Technology and Where Is it Really Headed?
Digital twins—virtual replicas of a physical product, process, or system—bridge physical and digital worlds. This article guides you through some of the most promising current and future use cases for digital twins.
For the past several years, the internet has been ringing with a new buzzword: digital twin. And, more recently, the term “digital twin of an organization (DTO)” has been added to the mix—as seen by Gartner’s move to add DTO to its list of top ten strategic technology trends for 2019.
As digital twins grow in complexity and move from being digital representations of single items to models of systems of interconnected things, more businesses are seeing the technology as an opportunity to orchestrate people, processes, and things in a sophisticated way, resulting in better business outcomes, as well as benefits for everyone. But is digital twin technology really here to stay? And where do its biggest opportunities lie for the future?
This article looks at what a digital twin really is, how to decipher true digital twins from the buzz, and where the technology is headed—especially as digital twins mature and expand in the scope.
At its simplest, a digital twin is a virtual replica of a physical product, process, or system. Digital twins act as a bridge between physical and digital worlds by using sensors to collect real-time data about a physical item. This data is then used to create a digital duplicate of the item, allowing it to be understood, analyzed, manipulated, or optimized. Other terms used to describe digital twin technology over the years have included virtual prototyping, hybrid twin technology, virtual twin, and digital asset management.
Although digital twins have been around for several decades, it’s only been since the rapid rise of IoT that they’ve become more widely considered as a tool of the future. Digital twins are getting attention because they also integrate things like artificial intelligence (AI) and machine learning (ML) to bring data, algorithms, and context together, enabling organizations to test new ideas, uncover problems before they happen, get new answers to new questions, and monitor items remotely.
Now that we’ve addressed the often elusive question, what is digital twin technology?, we can now explore how digital twin technology has been used to improve business processes. Digital twins were traditionally used to improve the performance of single assets, such as wind turbines or jet engines. In recent years, however, digital twins have become more sophisticated. Now, they connect not just one asset but rather systems of assets or even entire organizations. As digital twins bring together more and more assets and combine them with information about processes and people, their ability to help solve complex problems is also increasing.
A good example of where digital twins are being used at the organizational level is in health care. By creating a digital twin of a hospital, hospital administrators, doctors, and nurses can get powerful, real-time insight into patient health and workflows. Using sensors to monitor patients and coordinate equipment and staff, digital twins offer a better way of analyzing processes and alerting the right people at the right time when immediate action is needed.
