The digital twin, or virtual model of a physical process, is one of the biggest buzzwords in the business world right now. It has also become one of the most desired investments. According to IBM, the market for digital twin software is worth more than $3 billion as of 2020 and will continue to skyrocket until at least 2026, when it’s projected to be worth $48 billion.
Digital twin software is incredibly valuable to manufacturing plants in particular because the tool provides an in-depth virtual look at production processes and gathers data on the plant’s performance. Using this data, business leaders can test potential operational scenarios and study every detail of their processes from several angles.
One of the digital twin’s most notable achievements is the ability to give organizations a comprehensive look into the past, present, and future. It can use past performance to predict future issues or achievements, while also alerting you to current conditions in the plant. This kind of thorough reporting can give businesses the insight they need to make strategic decisions, address weaknesses, and even boost revenue.
The Past
To build an accurate model, the foundation of any manufacturing plant’s digital twin must be past production data. This should include quantifiable information on how each of your plant’s systems and machines operate, such as their average output and run time. It’s important to give the digital twin as much access to historical data as possible. This will help the model learn how your facility has typically operated up to this point so it can begin analyzing points of improvement and overlooked issues. Over time, as new data is continually gathered from current operations, the digital twin will keep an ongoing log of past performance that it can reference at any time.
The Present
In addition to analyzing past data, digital twin software will also process new information in real time from each point in your supply chain. As we mentioned earlier, this data will build on a historical log that forms the foundation that the software will use to predict achievements or disruptions moving forward. However, the digital twin will also use incoming information to provide engineers and operators with updated, real-world circumstances, which employees can utilize to recognize delays or potential production problems much sooner than they could otherwise. Additionally, they can use the digital twin to tweak production in real time to optimize efficiency and total output.
The Future
Thanks to the data gathered about both past and present plant performance, digital twins can then create a complex algorithm that predicts how the plant will perform in the future under a wide variety of circumstances. For example, if there’s a projected shortage of one raw material, the digital twin can test how plant processes will respond to different strategies for addressing the shortage. With this information, business leaders can make informed decisions on how to minimize disruptions and maintain plant output. For further testing, engineers can also use the model to test how plant performance will change with added investments, such as more employees or new equipment. On the opposite side, a digital twin can help predict when equipment or products should be retired or replaced in favor of more effective or profitable alternatives.
VirtECS® is a powerful process modeling and digital twin tool that can store and analyze in-depth plant parameters, including yields, rates, setup times, and process vessels. VirtECS® can then rapidly use the past and present data collected to explore future scenarios or potential process options to determine how the plant can optimize output. If you’re interested in learning more about digital twin analysis and the capabilities of VirtECS® in particular, download our short guide here.
