Often, the terms digital twin and simulation are used interchangeably. And in many ways, the two are remarkably similar. Digital twins and simulations use real-world data to replicate objects in a digital environment. But where they differ is in the scope of the digital model
Most simulations are designed to study only single, specific processes. Additionally, they tend to rely on deferred data which retains the value it was assigned at the time it was collected.
Digital twins can do much more. A digital twin creates an actual, working digital environment in which organizations can run a range of simulations to test and study many different processes. This is all informed by real-time data that provides a clear and up-to-date picture of what is happening right now. This data flows into the digital twin to ensure real-time accuracy, and any insights created by the processing system can also be sent back to optimize the subject.
Simply put, a simulation can offer a glimpse into the impact of changes made within a system. A digital twin takes things further, by providing detailed insights into what is currently happening within multiple systems or processes, and what is likely to happen in the future depending on which variables change.