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German Researchers Launch ChatGPT-based Part Vectorizer Tool for 3D Printing

March 26, 2024

A team led by Dr.-Ing. Sascha Hartig, known for his contributions to additive manufacturing, has introduced the “ChatGPT-based Part Vectorizer” tool. This innovative solution transforms the physical characteristics of parts into structured complexity vectors, facilitating manufacturing processes.

German Researchers Launch ChatGPT-based Part Vectorizer Tool for 3D Printing
A Funnel-Sieve, representing the Funnel-Sieve Model model.

The Part Vectorizer converts information such as part size, quality assurance levels, technical specifications, material class, and post-processing requirements into complexity vectors. These vectors, developed specifically for AM, utilize the OpenAI platform to create custom Generative Pre-trained Transformers (GPTs), eliminating the need for extensive programming knowledge.

“The Funnel-Sieve Model we developed combines Artificial Intelligence with advanced planning models, enabling precise control and adaptability to changing requirements,” Hartig explained in a recent LinkedIn post.

By standardizing the representation of key component attributes, the Part Vectorizer enhances production control within AM, offering a more efficient approach to manufacturing. This tool holds promise for streamlining workflows and optimizing resource allocation in the 3D printing industry.

Manufacturers and researchers alike can now access this tool to improve their AM processes and stay ahead in the rapidly evolving field of additive manufacturing. You can access the vectorizer at the OpenAI site, here.

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About the author | Phillip Keane
Phillip is an aerospace engineer from UK. He is a graduate of Coventry University (UK), International Space University (France) and Nanyang Technological University (Singapore), where he studied Advanced Manufacturing at the Singapore Centre for 3D Printing.
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