Digital Twins & Simulator Analytics: Unsung Heroes for Mercedes-AMG Petronas Motorsport
Blog: The Tibco Blog
If you’ve ever come out to one of our events or follow us on social media, then you’ve probably seen the Formula One
demo, which takes streaming data from the F1 2018 video game, analyzes it through Spotfire, and shows viewers their results in real-time.
Take that concept on a larger scale, sprinkle in an array of more complex technology and you get the highly advanced racing simulator that the Mercedes-AMG Petronas Motorsport team uses throughout the course of the season to test the best configurations and setup. What takes place in the simulator strongly impacts what happens on the actual race-day track; the right set-up, validated by the simulator, gives the drivers what they need to start on the grid.
The simulator is the closest the team gets to real-world track conditions, so it’s crucial that it is as technically granular and accurate as possible. Everything including graphics, seat adjustment, steering wheel, on-the-track sounds and crowd noises, and more are replicated to give the drivers the feeling they are driving on one of the circuits. And it’s the simulator and surrounding technologies that prove to be a winning combination.
But that’s not all; the simulator also acts as a digital twin, a virtual software replica of the same functionality that consistently produces better results and deeper insights for process optimization. Mercedes-AMG Petronas Motorsport has turned to TIBCO software, in particular, TIBCO Spotfire® visual analytics and TIBCO® Data Science software to constantly monitor new data as it becomes available for analysis.
Spotfire®’s data streams and connections to TIBCO Data Science are used to engineer features, predict parameters, and visualize results on streaming events. The software enables engineers to immediately sense, respond, and adjust the focus to the important combinations of parameters while streamlining the process, providing a centralized location for racing intelligence, rapid visualization, and interrogation of all current and accumulated data. In understanding the car and digging into the analysis, the team is able to improve its performance.
But Mercedes-AMG Petronas Motorsport isn’t the only company utilizing digital twin technology; in fact, it’s being utilized across a variety of industries such as manufacturing, energy, and healthcare. What the F1 simulator and all of its surrounding technology demonstrate is that If you are a technology or business leader, you can take 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 collaborative tech and business teams to make more informed decisions faster. This improves the odds of getting ahead in a very competitive business world – regardless of your industry.
Digital twins help companies like Mercedes-AMG Petronas Motorsport address their biggest data challenges. The end results include process optimization, insights into predictive and condition-based maintenance, and optimal business action based on the event stream.
To learn more about how Mercedes-AMG Petronas Motorsport uses TIBCO to help develop a digital twin simulator, read the full case study.
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