Though the end of 2015 is in sight, the NGRAIN team is continuing to make exciting advances in the world of augmented reality and the use of 3D scanning technology for visual inspection in the enterprise. To give you a sense for what the team has been up to, here is a brief primer on “geometric differencing.”

3D geometric differencing represents the ability to highlight and visualize the geometric differences between two 3D models. It is sometimes referred to as “geometry compare”. The most basic example of illustrating 3D geometric differencing can be seen below, where the left and right tires are “3D geometrically compared”, and the specific regions of difference is colored in green. Some of the differences can be difficult for the user to manually detect, thus an automatic way to detect it is very useful. This differencing can be visualized in 3D, so exact areas of difference can be seen from different perspectives.

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What are the components ended to achieve geometric differencing?

  • A voxel or point cloud engine (a part of our core technology and the NGRAIN SDK).
  • Ability to convert any geometry type (or format type) into either voxels or point cloud, where the voxel/point cloud structure represents the unifying format to do 3D geometric differencing.
  • Ability to compare a region of space between one model to another model – in the image below, a voxel is compared against the corresponding voxel in the other 3D model, and any difference in the voxel can be highlighted (in green in the image below).

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How does NGRAIN envision geometric differencing being used in the enterprise?

Version Control

  • In general, just like you can visualize the “diff” between two versions of source code, you can visualize geometric differences between two versions of the 3D model, as illustrated by the first image in this blog. This is why we prefer the term “geometric difference” as opposed to “geometry compare”.
  • CAD: when engineers modify components, they rarely communicate the differences for downstream needs (e.g. needs such as technical writing, training, etc.). Thus downstream staff takes a lot of manual time to identify what has changed – geometric differencing allows a full-proof and automatic way of detecting the changes.
  • DCC: with large productions, there are usually multiple modelers working on the same scene, and may cause inadvertent errors (e.g. accidentally clicked and moved a single vertex by a small amount) in the models. By doing 3D geometric differences, before scenes are integrated between different modelers, the supervisor is 100% sure that all the expected versions are integrated correctly.

Validating between Converted Formats

  • There are often cases where we send data files of a specific type to another person, resulting in a data conversion from one 3D format to another. However, there is never any assurance that the converted result is geometrically the same as the original. By converting both data files into voxels/point cloud, and doing 3D geometric differencing, we can be sure that the representation is correct geometrically. Sometimes the difference may lie in the tessellation techniques applied.

As-designed versus As-built

  • A CAD model can be geometrically differenced with a scan of the live model, by converting both to the unified voxel/point cloud form.

MRO Procedural Tasks

  • Augmented Reality (AR): in walking through a maintenance procedure in an AR deployment, the mechanic’s actions are never verified as to the correctness of each task step. With an appropriate scanner and geometric differencing (between the previous and current scan of the task steps), the mechanic’s actions can be validated as he works through the entire maintenance procedure.
  • Content Creation: currently, creating the 3D content for a maintenance procedure (in a VR or AR deployment) can be time consuming. With an appropriate scanner and geometric differencing at each task step (between the previous scan and current scan of the task steps), the 3D content creation needed for the entire sequence can be much faster and very accurate.

Of course, the devil is in the details, and there are plenty of devils. There is a lot of potential for 3D geometric differencing in our core technology and we are excited about the possibilities this brings for industrial markets like aerospace, energy, and manufacturing!

What do you think? Is this the tech you’ve been waiting for? Get in touch with us — we want to hear from you!