Physna
Software : Engineering : Digital Twin
Every day, manufacturing and design firms spend countless hours trying to identify working 3D models and objects, re-designing others from scratch, or buying more products just because they can’t find what they’re looking for. Physna eliminates wasted search hours by using your model’s unique object geometry to index your data in a way that makes every model easy to search — and easy to find. That means less time hunting and more time developing the products and services your customers love.
Assembly Line
3D Search Unlocks Part Database Potential
A variety of digital formats can be leveraged as input, anything from CAD files to photographs, with the system’s algorithms that the Physna team developed creating a “digital fingerprint” of the 3D object. This fingerprint describes the object and enables the user to search a database of parts using a 3D part as the search term.
Physna is capable of interpreting assemblies and the parts associated with the assembly. In the 3D viewer, the user is able to inspect the assembly and search for similar parts from the database.
For instance, if an engineer at has modeled a flange that features a 1-inch ID, a common search using language would be “1-inch flange”, but if the engineer uploaded the model to Physna, the fingerprint would include aspects of the flange like its bolt pattern, whether or not it incorporated a bearing and contours of the flange design. This may lead to discovery of previously designed parts or even compatible third party parts if the database is connected to other vendors.
Physna raises $20 million for AI that analyzes and digitizes 3D objects
Physna, a Cincinnati, Ohio-based startup developing an AI-powered 3D modeling platform for industrial engineering, today announced that it raised $20 million. The company says the funds will be used to grow its team and increase development as new customers sign on.
It’s often difficult to search using the 3D model of a physical part, such as a CAD model or a 3D scan — especially when the part is a component of something larger (e.g., matching a screw to an assembly). Traditionally, solutions have been costly and time-consuming, impacting processes not only during engineering procurement but parts identification. It’s estimated that while over 70% of the economy is centered around physical goods, less than 1% of software is capable of handling 3D data.