CADGen: Computer‐aided design sequence construction with a guided codebook learning

Abstract Computer‐aided design (CAD) software continues to be a crucial tool in digital twin application and manufacturing, facilitating the design of various products. We present a novel CAD generation method, an agent that constructs the CAD sequences containing the sketch‐and‐extrude modelling operations efficiently and with high quality. Starting from the sketch and extrusion operation sequences, we utilise the transformer encoder to encode them into different disentangled codebooks to represent their distribution properties while considering their correlations. Then, a combination of auto‐regressive and non‐autoregressive samplers is trained to sample the code for CAD sequence construction. Extensive experiments demonstrate that our model generates diverse and high‐quality CAD models. We also show some cases of real digital twin applications and indicate that our generated model can be used as the data source for the digital twin platform, exhibiting designers' potential.

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Publication Details

Journal
Digital twins and applications.
Published
2024-09-01
DOI
https://doi.org/10.1049/dgt2.12014
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

CADGen: Computer‐aided design sequence construction with a guided codebook learning

Bin Zhou, Zhuqing Li, Shengdi Zhou, Xiaoqiang Zan
Digital twins and applications.
Manufacturing Process and Optimization
article

CADGen: Computer‐aided design sequence construction with a guided codebook learning

Bin Zhou, Zhuqing Li, Shengdi Zhou, Xiaoqiang Zan
article en

Abstract

Abstract Computer‐aided design (CAD) software continues to be a crucial tool in digital twin application and manufacturing, facilitating the design of various products. We present a novel CAD generation method, an agent that constructs the CAD sequences containing the sketch‐and‐extrude modelling operations efficiently and with high quality. Starting from the sketch and extrusion operation sequences, we utilise the transformer encoder to encode them into different disentangled codebooks to represent their distribution properties while considering their correlations. Then, a combination of auto‐regressive and non‐autoregressive samplers is trained to sample the code for CAD sequence construction. Extensive experiments demonstrate that our model generates diverse and high‐quality CAD models. We also show some cases of real digital twin applications and indicate that our generated model can be used as the data source for the digital twin platform, exhibiting designers' potential.

Digital twins and applications.Vol. 1(1)
Beihang University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Beijing Science and Technology Planning Project
Industry, innovation and infrastructure
Openalex Percentile: Top 80%
Manufacturing Process and Optimization
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CADGen: Computer‐aided design sequence construction with a guided codebook learning — Bin Zhou, Zhuqing Li, et al. · Digital twins and applications. (2024) | TGRS Research Map | TGRS