Artificial intelligence and big data in the production process to optimise the parameters of the cut tobacco-making process

Wenlong Jin, Liujing Wang and Chengting Zhang

International Journal of Information Technology and Management, 2023, vol. 22, issue 3/4, 315-334

Abstract: With the development of industrial control technology and the acceleration of informatisation construction, the tobacco industry has higher and higher requirements for the scheduling, quality, craftsmanship, and consumption of tobacco production lines. This article aims to use big data and artificial intelligence energy systems to optimise the parameters in the cut tobacco-making process. This paper designs a making process detection system based on artificial intelligence, and uses a database to store big data. It analyses the data through the database, selects an important step in the cut tobacco-making process, and optimises the parameters of threshing and redrying. The speed of beater, hot air temperature and moisture regain temperature in the threshing and redrying process were compared and analysed. Finally, the leaf emergence rate and stem emergence rate are compared between the tobacco shreds with optimised parameters and the unoptimised shredded tobacco. The results show that the optimised parameters are 550, hot air temperature 90°C, and moisture regain temperature 65°C. Additionally, the optimised shredded tobacco has stronger performance than the unoptimised shredded tobacco.

Keywords: artificial intelligence and big data; cut tobacco-making process; parameter optimisation; optimisation process. (search for similar items in EconPapers)
Date: 2023
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