Modeling and Optimization for Automobile Mixed Assembly Line in Industry 4.0

Autor: Lixiong Gong, Bingqian Zou, Zhiqun Kan
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Journal of Control Science and Engineering, Vol 2019 (2019)
Druh dokumentu: article
ISSN: 1687-5249
1687-5257
DOI: 10.1155/2019/3105267
Popis: Industry 4.0 promotes the development of traditional manufacturing industry to digitization, networking, and intellectualization. Smart factory is composed of network that includes production equipment, robot, conveyor, and logistics system. According to the characteristics of the mixed flow assembly, a simulation platform of automobile mixed flow assembly is built based on industry 4.0 in the paper, which operates and manages automobile assembly, logistics warehouse, and CPS effectively. On this basis, FlexSim software is adopted to establish the auto-mixed assembly model that finds out the bottleneck of auto-mixed assembly problem. By means of parameter adjustment, rearrangement, and merger of process, the whole assembly time of the 500 automobiles dropped by 33 hours, the equipment utilization rate increased by 20.19%, and the average blocked rate decreased by 21.19%. The optimized results show that the proposed model can greatly increase manufacturing efficiency and practical application in industry 4.0.
Databáze: Directory of Open Access Journals
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