Everyone wishes they knew what was going to happen in the future, so they could better position themselves for favorable outcomes and avoid the anxiety’s that comes with uncertainty. For industrial operations, the ability to effectively predict future performance, and proactively manage accordingly, is akin to an operational crystal ball with nearly unlimited potential.

At Bsquare, we see Digital Twins as one of the critical next steps in the digital transformation progression towards accurate, meaningful prediction of future events . While conventional industrial Internet of Things (IIoT) solutions refer to Digital Twins as digital models of real-world devices, we take the concept a critical step further.

In order to predict the condition of an asset down the road, say next week, it’s necessary to transcend a pretty dashboard view of a device’s current anatomy, and truly understand its behavior. What conditions and events influence it to change, to regress or thrive, from one environmental state to another? Questions like these and the insights they deliver dictate meaningful forecasting, not CAD animations of a device’s present state as suggested by many in the IIoT space.

Understanding these behavioral patterns, and leveraging advanced machine learning algorithms, enables meaningful Digital Twins to be played forward or backward in time. This modeling allows operators to better understand how a device might perform in a certain scenario, for example, to alleviate a potential mechanical failure before it happens.

As the IIoT landscape continues to take form, it will be imperative for progressive industrial organizations to leverage the behavioral insights Digital Twins can provide, if they wish to truly harness the future’s potential and lead their respective packs.

Watch this video for a two-minute summary of Bsquare’s take on Digital Twins.

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