Modifying a factory process can create confusing bills from the company's accountants, but what if the process changes led to even more chaotic problems? For engineers working in manufacturing, being able to look at a set of possible modifications before implementing them in an actual system would help reduce headaches and wasted time. Digital twins are capable of doing exactly that by linking together a virtual model and real-world information from sensors.

What Is a Digital Twin?

A digital twin is the combination of a virtual model with real-world data about a physical system it represents, making it possible for the model to display information about the target's operation and environment. According to IBM, they can be formed using data provided by sensors on the target equipment about its pressure, temperature, and other variables. This capacity for information collection gives digital twins an advantage over typical virtual models.

A digital twin is not merely an image of the target, because it receives data that keeps it up to date.

How Are Digital Twins Useful?

When presented with a scenario in which a machine in a factory started vibrating abnormally, IBM recommends that engineers make use of the digital twin. Programmed with all of the information about the machine's past and current state, they can look at how the process modifications suggested as solutions to the vibration problem will influence the target. The article lists this application and the prevention of maintenance issues using this analytical tool as two of its key potential uses in the manufacturing industry. Its ability to analyze possible modifications assists engineers in understanding what they intend to change.

The model acts as an experiment, letting individuals attempt modifications on a virtual copy of an object before attempting anything irreversible on the actual thing.

The report on digital twins from the National Institute of Standards and Technology lists July 2026 as a month in which three roundtable meetings have occurred for the project. Delegates were able to identify the potential for these analytical tools to aid in product design, manufacturing, and production lifecycle management. As the group examined the possibilities, the discussion continued to the issues associated with cybersecurity, system integration, and model accuracy. These shortcomings contribute to the necessity for the cautious examination advised by the NIST before accepting results generated by these virtual models. While the NIST publication provides insight regarding the qualities to consider when choosing an analytical tool designed to represent the real world, those looking into the potential uses of a digital twin must ask questions and test its credibility as well as the accuracy of its data. One must understand a

model's reliability, and it must be proved as trustworthy for the given purpose, and consider the likelihood of uncertainty affecting the accuracy of its results.

Why Do I Care About This?

Digital twins create the opportunity for experimentation with modifications to real-world objects' virtual copies in an effort to observe the effects of these alterations. The key element which makes these products potentially useful lies in providing the information necessary to make informed decisions about modification and application. Like all other analytical tools, individuals must pursue accuracy and reliability during application, and recognize uncertainties which may influence their outcomes and interfere with the desired degree of certainty.

Sources

IBM. What Is a Digital Twin? . 2026.

NIST. Digital Twins Workshops Summary Report . 2026.