Just getting familiar with the digital thread? You’ve come to the right place to learn what it is and why you need it for your products.
A digital thread is the uninterrupted connection of information related to a product, or any of its components.
To get there, you have to capture, and keep connected, every relevant piece of digital data created about your product.
For example, one end of a digital thread might be a list of requirements. Until someone tried to meet a requirement, there was no product concept, so the thread starts there—with a requirement.
Along the thread, we want to capture anything that helps further describe the product. For example, what is the functional breakdown of how those requirements will be met? That breakdown (which may turn into a product structure or BoM) is part of the digital thread.
The shape and size of a component (3D geometry) is another part of the thread.
The tolerances and other desired manufacturing characteristics are another part (regardless of whether they are PMI on a 3D model or annotations on a 2D drawing).
And the thread doesn’t end with the intent. It continues with the execution.
If a CAM program is written to cut the part out of raw material, that’s part of the thread.
If an inspection drawing is made to govern the quality assurance of the part, not only is that drawing part of the thread, but so is the data recorded by the inspector.
This keeps going for any data captured throughout the life of the product.
All of this data is part of the digital thread.
Maybe you noticed something in that last example. Up until inspection, one digital thread covered many physical parts. But once you start talking about inspection data, or service data, or even IoT data captured after the product is sold, you’re now getting data for specific physical instances.
Given this, you can see how Big Data and analytics apply back to product development—if, in fact, the digital thread is relevant for you.
Why do you need a digital thread for your products?
You need the digital thread so that you can construct a digital twin—the virtual representation of a physical instance of the product.
You need the digital twin to track, share and discuss your product.
So you need to know the requirements, the intent, the design, the simulated performance, and the manufacturing plan, as well as the as-built (inspection), the as-maintained (over the life of the product), and the performance data (collected from sensors, via the IoT) to create your digital twin—and capture future instances of it.
Until robust 3D modeling was possible, complex finite-element calculations to predict product performance would never have been considered.
But once virtual simulation was possible, then suddenly digital “behavior” modeling was introduced.
Inspection technologies that capture point clouds describing the surface of a physical object have made it possible to define the shape of the actual physical instance rather than of the ideal (as-designed) physical instance.
This cycle will keep repeating.
Our digital twins will always be an approximation of the real thing, but our “models” will share a tighter fidelity with the physical instance as the accuracy loop closes between design and final inspection.
Today’s increasing reliance on digital twins and the digital thread is really a recognition that advances in PLM, metrology, behavior modeling, IoT and Big Data have reached a critical mass.
When synthesized, these interconnected tools yield an amazing new capability to deliver instance-specific performance prediction, which helps lead to product excellence, satisfied customers and market leadership.
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