P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study
To overcome the problems of long production cycle and high cost in the product manufacturing process, a P2P (platform to platform) cloud manufacturing method based on a personalized custom business model has been proposed in this paper by integrating different technologies such as deep learning and...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/6/3129 |
| _version_ | 1797609077828747264 |
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| author | Dian Huang Ming Li Jingfei Fu Xuefei Ding Weiping Luo Xiaobao Zhu |
| author_facet | Dian Huang Ming Li Jingfei Fu Xuefei Ding Weiping Luo Xiaobao Zhu |
| author_sort | Dian Huang |
| collection | DOAJ |
| description | To overcome the problems of long production cycle and high cost in the product manufacturing process, a P2P (platform to platform) cloud manufacturing method based on a personalized custom business model has been proposed in this paper by integrating different technologies such as deep learning and additive manufacturing (AM). This paper focuses on the manufacturing process from a photo containing an entity to the production of that entity. Essentially, this is an object-to-object fabrication. Moreover, based on the YOLOv4 algorithm and DVR technology, an object detection extractor and a 3D data generator are constructed, and a case study is carried out for a 3D printing service scenario. The case study selects online sofa photos and real car photos. The recognition rates of sofa and car were 59% and 100%, respectively. Retrograde conversion from 2D data to 3D data takes approximately 60 s. We also carry out personalized transformation design on the generated sofa digital 3D model. The results show that the proposed method has been validated, and three unindividualized models and one individualized design model have been manufactured, and the original shape is basically maintained. |
| first_indexed | 2024-03-11T05:56:28Z |
| format | Article |
| id | doaj.art-a68e3306333a48da829463d0957b6bd3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T05:56:28Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a68e3306333a48da829463d0957b6bd32023-11-17T13:46:21ZengMDPI AGSensors1424-82202023-03-01236312910.3390/s23063129P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory StudyDian Huang0Ming Li1Jingfei Fu2Xuefei Ding3Weiping Luo4Xiaobao Zhu5School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, ChinaSchool of Information Engineering, Nanchang Hangkong University, Nanchang 330063, ChinaSchool of Information Engineering, Nanchang Hangkong University, Nanchang 330063, ChinaSchool of Information Engineering, Nanchang Hangkong University, Nanchang 330063, ChinaSchool of Information Engineering, Nanchang Hangkong University, Nanchang 330063, ChinaSchool of Information Engineering, Nanchang Hangkong University, Nanchang 330063, ChinaTo overcome the problems of long production cycle and high cost in the product manufacturing process, a P2P (platform to platform) cloud manufacturing method based on a personalized custom business model has been proposed in this paper by integrating different technologies such as deep learning and additive manufacturing (AM). This paper focuses on the manufacturing process from a photo containing an entity to the production of that entity. Essentially, this is an object-to-object fabrication. Moreover, based on the YOLOv4 algorithm and DVR technology, an object detection extractor and a 3D data generator are constructed, and a case study is carried out for a 3D printing service scenario. The case study selects online sofa photos and real car photos. The recognition rates of sofa and car were 59% and 100%, respectively. Retrograde conversion from 2D data to 3D data takes approximately 60 s. We also carry out personalized transformation design on the generated sofa digital 3D model. The results show that the proposed method has been validated, and three unindividualized models and one individualized design model have been manufactured, and the original shape is basically maintained.https://www.mdpi.com/1424-8220/23/6/3129personalized business modelP2P cloud manufacturingreverse engineeringdeep learning3D reconstruction3D printing |
| spellingShingle | Dian Huang Ming Li Jingfei Fu Xuefei Ding Weiping Luo Xiaobao Zhu P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study Sensors personalized business model P2P cloud manufacturing reverse engineering deep learning 3D reconstruction 3D printing |
| title | P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study |
| title_full | P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study |
| title_fullStr | P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study |
| title_full_unstemmed | P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study |
| title_short | P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study |
| title_sort | p2p cloud manufacturing based on a customized business model an exploratory study |
| topic | personalized business model P2P cloud manufacturing reverse engineering deep learning 3D reconstruction 3D printing |
| url | https://www.mdpi.com/1424-8220/23/6/3129 |
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