Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs
Light small-sized, multi-rotor UAVs, with their notable advantages of portability, intelligence, and low cost, occupy a significant share in the civilian UAV market. To further reduce the full lifecycle cost of products, shorten development cycles, and increase market share, some manufacturers of th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/7/12/698 |
| _version_ | 1797381396059127808 |
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| author | Yongjie Zhang Yongqi Zeng Kang Cao |
| author_facet | Yongjie Zhang Yongqi Zeng Kang Cao |
| author_sort | Yongjie Zhang |
| collection | DOAJ |
| description | Light small-sized, multi-rotor UAVs, with their notable advantages of portability, intelligence, and low cost, occupy a significant share in the civilian UAV market. To further reduce the full lifecycle cost of products, shorten development cycles, and increase market share, some manufacturers of these UAVs have adopted a series development strategy based on the concept of commonality in design. However, there is currently a lack of effective methods to quantify the commonality in UAV designs, which is key to guiding commonality design. In view of this, our study innovatively proposes a new UAV commonality evaluation model based on the basic composition of light small-sized multi-rotor UAVs and the theory of design structure matrices. Through cross-evaluations of four models, the model has been confirmed to comprehensively quantify the degree of commonality between models. To achieve commonality prediction in the early stages of multi-rotor UAV design, we constructed a commonality prediction dataset centered around the commonality evaluation model using data from typical light small-sized multi-rotor UAV models. After training this dataset with convolutional neural networks, we successfully developed an effective predictive model for the commonality of new light small-sized multi-rotor UAV models and verified the feasibility and effectiveness of this method through a case application in UAV design. The commonality evaluation and prediction models established in this study not only provide strong decision-making support for the series design and commonality design of UAV products but also offer new perspectives and tools for strategic development in this field. |
| first_indexed | 2024-03-08T20:50:53Z |
| format | Article |
| id | doaj.art-8e21d67b673742d0bc1d84b7e1a09325 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-08T20:50:53Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-8e21d67b673742d0bc1d84b7e1a093252023-12-22T14:03:59ZengMDPI AGDrones2504-446X2023-12-0171269810.3390/drones7120698Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVsYongjie Zhang0Yongqi Zeng1Kang Cao2Civil Aviation School, Northwestern Polytechnical University, Xi’an 710072, ChinaCivil Aviation School, Northwestern Polytechnical University, Xi’an 710072, ChinaCivil Aviation School, Northwestern Polytechnical University, Xi’an 710072, ChinaLight small-sized, multi-rotor UAVs, with their notable advantages of portability, intelligence, and low cost, occupy a significant share in the civilian UAV market. To further reduce the full lifecycle cost of products, shorten development cycles, and increase market share, some manufacturers of these UAVs have adopted a series development strategy based on the concept of commonality in design. However, there is currently a lack of effective methods to quantify the commonality in UAV designs, which is key to guiding commonality design. In view of this, our study innovatively proposes a new UAV commonality evaluation model based on the basic composition of light small-sized multi-rotor UAVs and the theory of design structure matrices. Through cross-evaluations of four models, the model has been confirmed to comprehensively quantify the degree of commonality between models. To achieve commonality prediction in the early stages of multi-rotor UAV design, we constructed a commonality prediction dataset centered around the commonality evaluation model using data from typical light small-sized multi-rotor UAV models. After training this dataset with convolutional neural networks, we successfully developed an effective predictive model for the commonality of new light small-sized multi-rotor UAV models and verified the feasibility and effectiveness of this method through a case application in UAV design. The commonality evaluation and prediction models established in this study not only provide strong decision-making support for the series design and commonality design of UAV products but also offer new perspectives and tools for strategic development in this field.https://www.mdpi.com/2504-446X/7/12/698light and small multi-rotor UAVscommonality evaluationdesign structure matrixconvolutional neural networkcommonality prediction |
| spellingShingle | Yongjie Zhang Yongqi Zeng Kang Cao Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs Drones light and small multi-rotor UAVs commonality evaluation design structure matrix convolutional neural network commonality prediction |
| title | Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs |
| title_full | Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs |
| title_fullStr | Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs |
| title_full_unstemmed | Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs |
| title_short | Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs |
| title_sort | commonality evaluation and prediction study of light and small multi rotor uavs |
| topic | light and small multi-rotor UAVs commonality evaluation design structure matrix convolutional neural network commonality prediction |
| url | https://www.mdpi.com/2504-446X/7/12/698 |
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