Posted by Digital Engineering 24/7—AMC Bridge’s latest technology demonstration, Similar Parts Search, explores how combining artificial intelligence (AI) with advanced 3D geometric processing can address these challenges and improve the discovery, reuse, and evaluation of structurally similar parts across engineering workflows.
By leveraging learned geometric representations of 3D models, the POC enables consistent, geometry‑aware similarity detection across large repositories, independent of how parts are named or categorized.
The Similar Parts Search technology demonstration combines Graph Neural Networks (GNNs) with advanced 3D geometric processing to enable similarity detection within large collections of engineering models. This approach allows the system to learn and leverage geometric characteristics of 3D parts.
By automatically preparing uploaded 3D models for analysis and generating persistent digital profiles for each part, the system supports scalable, reusable similarity searches across datasets. This foundation enables the technology to be extended into custom, production‑ready solutions that can integrate with existing CAD, PLM, ERP, or supply‑chain systems.
The demonstration leverages domain‑specific datasets, established expertise in geometric algorithms, and engineering model collections, including the Mechanical Components Benchmark (MCB)—an open‑source dataset developed by Purdue University and distributed under the MIT License.
The POC highlights how AI‑based geometric similarity search can deliver tangible operational and economic benefits across engineering, manufacturing, and supply‑chain domains. By enabling faster identification of previously manufactured or equivalent parts, Similar Parts Search supports quicker manufacturing cost and lead‑time estimation.
The prototype demonstrates the potential to reduce part proliferation and stock variation by minimizing near‑duplicate components across product lines. Improved similarity detection also contributes to lower warehouse and inventory holding costs through consolidation and reuse strategies, simplifies supply and procurement management via greater standardization, and enhances design reuse.
By pairing AI‑driven similarity metrics with intuitive visual validation, the demonstration supports human‑in‑the‑loop decision‑making. To see the current functionality of the Similar Parts Search technology demonstration, watch a short demo video.
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