Three-dimensional Modeling and Rapid Prototyping of the Sake Bottle Based on Reverse Engineering
Authors: 
Shuaishuai Lv, Kaifeng Du, Hongjun Ni, Xingxing Wang, Yu Zhu, Yi Lu, Hai Gu, Yuanyuan XuAuthors Info & Claims
Article No.: 12, Pages 1 - 5
Abstract
Sake bottle was analyzed and improved based on reverse engineering and rapid prototyping technology. According to the structural characteristics of the selected sake bottle, the digital information of the model was collected by means of a three-dimensional laser scanner. Combined with the idea of reverse design, the space surface and entity model of the sake bottle were reconstructed based on Imageware and Solidworks software. Eventually, we used rapid prototyping technology to export entity of the sake bottle model. The combination of reverse engineering and rapid prototyping technology simplifies the process of product optimization and effectively shortens the design and the development cycle of the product.
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Index Terms
- Three-dimensional Modeling and Rapid Prototyping of the Sake Bottle Based on Reverse Engineering
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Published In
October 2019
418 pages
ISBN:9781450372022
DOI:10.1145/3358331
Copyright © 2019 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 October 2019
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- Research-article
- Research
- Refereed limited
Funding Sources
- Key Research and Development Program of Jiangsu (Industry Prospects and Common Key Technologies?
- Nantong Science and Technology Commission of China
- Nantong Key Laboratory of 3D printing technology and Application
- Qing Lan Project of Jiangsu Province
- Priority Academic Program Development of Jiangsu Higher Education Institutions
- Jiangsu Wall Material Innovation Research Project
- Nantong Applied Research Project
- Teaching Reform Project of Nantong University
- Priortity Discipline Construction Program of Jiangsu Province
Conference
AIAM 2019
AIAM 2019: 2019 International Conference on Artificial Intelligence and Advanced Manufacturing
October 17 - 19, 2019
Dublin, Ireland
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Overall Acceptance Rate 100 of 285 submissions, 35%
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