The idea of simulation and modeling has been around for a long time. But, the rise in the use of advanced analytics and the Internet of Things (IoT) today have evolved this into the concept of the digital twin. It’s the idea of having a virtual digital model of a physical system that is used to make better decisions about the real world physical system. Digital twins are usually intertwined with sensors and include a two-way interaction between the physical and digital twin. While it’s one of the hottest concepts in technology, is your business really ready to take advantage of one?
Digital twins are utilized in three main ways:
- To prototype and iteratively test and design what the product could be before it’s produced in addition to design optimization
- To monitor the performance of the physical asset and intervene in the operation if needed
- To collect data off of a fleet of a particular type of product or asset (called aggregate twins) and create an approximation of those devices, which could support things like predictive maintenance
Digital twins can range from being pretty simple asset twins to increasingly sophisticated and ambitious twins. They are used across various industries for a number of different use cases. In healthcare, a patient digital twin is used to monitor how a patient could respond to different treatments, and if intervention is needed. More sophisticated twins are being used to model cities, taking into account traffic, transit, power consumption, and pollution.
While it sounds great, implementing one isn’t always straightforward. There are a number of elements to consider: What is the problem and is a digital twin a fit? Is it sustainable? Is it an expensive version of what could be a report? Is it real-time? The bottom line is that you need to start with a sound business case that looks at the value of having a digital twin—typically driven by the use case.
In the case of Mercedes-AMG Petronas Formula One, the use case is pretty straightforward: create a simulation that mimics the real track experience and acts as a digital twin to maximize the benefits of limited on-track testing time. The purpose of the simulator is to help the team set up the car to run faster, to rapidly advance car development, and to increase the team’s ability and speed to fine-tune advancements during the season. It is also used to find out where the team needs to improve, where its competition is the strongest, where the team has weaknesses, and the performance areas to advance. Additionally, an F1 simulator also provides a driver’s first opportunity to test new design features and understand how they will affect performance before going on to the track.
Once you determine the purpose and the value-add to your digital twin, you can then establish a “data to decisions cycle”, which ultimately means picking and choosing the data you want to capture from the twin in order to gain the business value and success from it.
Data is at the core of Mercedes-AMG Petronas Formula One’s simulation work. The team needs to quickly filter through the data to identify the optimal setup among millions of combinations. This involves interactive visual analytics, data science, and what-if scenarios to optimize car balance and setup parameters. Target values and parameters are tracked throughout the season. When performance in a particular race is sub-optimal there is more headroom to optimize the configuration for the next race.
If you are a technology or business leader, you can gather a vast amount of data in a short period of time, visualize it, and run machine learning algorithms to derive insights and patterns that enable teams to collaborate and make more informed decisions faster. This improves the odds of getting ahead in a very competitive business world. Digital twins produce better results and deeper insights for operational optimization. The end result? Better processes, insights, and optimal business action, giving you a competitive advantage of your own.Digital twins are one of the hottest concepts in technology, but is your business really ready to take advantage of one? Click To Tweet
Learn how Mercedes-AMG Petronas F1 has implemented a digital twin to help maximize its on-track performance. And, listen to our TIBCO Talks podcast episode for a deep dive conversation on digital twins with TIBCO’s global CTO, Nelson Petracek, and Doug Henschen, the vice president, and principal analyst at Constellation Research.