CASTOR
CASTOR has released the latest innovation to its parts identification software, the ability to automatically analyse 2D drawings, both technically and economically, to provide recommendations on 3D printing.
The new software uses a set of geometric and economic analyses. Automatic parts identification for 3D printing is possible using designers’ 2D drawings, even when 3D CAD files are not at reach.
This solves a problem many companies face, especially if they rely on 2D drawings that are decades old, which made it difficult and time-consuming to determine which of their parts could be 3D printed, as beforehand, the process was completely manual and complex.
The technology behind CASTOR’s 2D analysis is based on computer vision that interprets the geometry and product manufacturing information (PMI) of each part, and machine learning models that have gained deeper insights and improved over time due to the vast number of parts that are uploaded to CASTOR on a daily basis.
“We give these organisations a tool that helps them find new business cases and discover opportunities to reach their initiatives and 3D printing goals, using their existing 2D design files,” said Omer Blaier, Co-Founder and CEO of CASTOR.
The analysis can expose different opportunities, which is ideal when tackling legacy products or building an AM spare parts programme. The software enables thousands of parts from 2D drawings at once.
Once parts are uploaded it automatically extracts PMI out of PDF files of 2D drawings and calculates parts’ size, volume and complexity, based on dimensions from projected views. It then suggests 3D printability of parts, recommends optimal technology and materials, and performs a financial analysis of additive manufacturing compared to traditional manufacturing.
Once the selected files are in a 3D format, the software can deliver recommendations for re-designing parts for additive manufacturing, such as part consolidation and weight reduction. The various technical analyses include size and tolerance checks, cost breakdown and lead time estimation.
