1. A digital modeling framework for the motorcycle industry with advanced computer design
- Author
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Su Qiang, Shen Changqun, Guanqin Wang, Xiufeng Tan, Youxiang Zhang, Li Jianghong, and Ping Wang
- Subjects
0209 industrial biotechnology ,Data processing ,Product design ,Computer science ,Process (computing) ,Word error rate ,02 engineering and technology ,computer.software_genre ,Automotive engineering ,Theoretical Computer Science ,Product (business) ,020901 industrial engineering & automation ,0202 electrical engineering, electronic engineering, information engineering ,Production (economics) ,020201 artificial intelligence & image processing ,Geometry and Topology ,computer ,Software ,Data integration ,Parametric statistics - Abstract
A digital modeling framework for motorcycles (DMF) involves applying advanced computer design, computer-assisted analysis, and computer-assisted development. Data processing technology simulated prototype product, fast prototype technology, standard technology, etc. It is an interdisciplinary, systematic technology in the entire process of product design, production, and manufacture. DMF solves single-model production and constrained capacity building to satisfy the industry's demand for individual and diverse motorcycle goods. DMF sets forward several approaches within it, including parametric technologies for design, technology dependent on experience, design application, and data integration trends. The DMF provides the basis for a synthesis of motorcycles' production and demand. The result illustrates that digital concept strategies and approaches can be used in the motorcycle industry in reality with the highest efficiency (97.32%), emission rate (25.16%), speed rate (95.23%), exhaust rate (41.32%), heat loss rate (6.18%), performance metrics rate (9.32%), and error rate (5.44%), compared to other popular methods. For the 100 motorcycles, the average charging capacity, speed, distance traveled, and implementation cost ratio are observed at 97.11%, 85–100 km/h, 80–100 km, and 9.32%, respectively.
- Published
- 2021