DYNDRITE DEBUTS ADDITIVE MANUFACTURING TOOLKIT BUILD PROCESSOR, PARTNERS WITH RENISHAW

3dprintingindustry.com | November 19, 2019

Dyndrite Corporation, a Seattle-based software company, has introduced the Additive Manufacturing Toolkit (AMT) and accelerated production preparation build processor for 3D printing.AMT is based on the company’s Accelerated Computation Engine (ACE), a GPU-powered geometry kernel, and is capable of importing native CAD files for maximum quality of 3D printed output. It also features an integrated Python application programming interface (API) for customizable scripting of interactive, automated workflows.The Dyndrite Accelerated Computation Engine is a genuine paradigm shift and promises to do for 3D printing what Adobe and PostScript did for 2D printing in the 1980s,” said Harshil Goel, founder and CEO of Dyndrite.
The Dyndrite Additive Toolkit enables a streamlined CAD-to-Print workflow for industrial additive manufacturing. Users can manage terabytes of manufacturing data, print higher-order geometries and adjust parts in-situ to increase both throughput and quality. The AMT build processor is said to leverage modern methodologies to meet the requirements of production-oriented customers in the aerospace, medical, automotive, energy and service bureau markets.

Spotlight

Business demands have forced manufacturers to be more agile. Smart manufacturers are adopting technology, specifically digital twins, to move faster. Using a digital twin in a manufacturing environment can fast-track discovering bottlenecks, drive efficiencies, lower costs, reduce environmental footprint, and help manage risk. However, there is mystery around digital twins, from defining what they are and their strengths to the critical importance of an ecosystem approach to address the diversity of digital twin scenarios. The goal of this paper is to demystify digital twins, so more manufacturers can apply the technology and bring agility to their operations.


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Spotlight

Business demands have forced manufacturers to be more agile. Smart manufacturers are adopting technology, specifically digital twins, to move faster. Using a digital twin in a manufacturing environment can fast-track discovering bottlenecks, drive efficiencies, lower costs, reduce environmental footprint, and help manage risk. However, there is mystery around digital twins, from defining what they are and their strengths to the critical importance of an ecosystem approach to address the diversity of digital twin scenarios. The goal of this paper is to demystify digital twins, so more manufacturers can apply the technology and bring agility to their operations.

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