System and method for improving production stability of cut tobacco dryer

Abstract

The invention relates to a system and a method for improving the production stability of a cut tobacco dryer, and belongs to the technical field of cut tobacco production. The system comprises a dataacquisition module, a data processing module, a stability evaluation module, an early warning and optimization module, a steady-state real-time analysis and evaluation module, an unsteady-state automatic control judgment module, an unsteady-state real-time analysis and evaluation module and the like. According to the system, new-generation information technologies such as industrial big data and artificial intelligence are used as supports, the unsteady-state time is shortened, the steady-state control quality is improved, then the quality stability of the whole production process of the cut tobacco dryer is effectively improved, and the system is easy to apply and popularize.

Description

technical field [0001] The invention belongs to the technical field of tobacco shredded production, and in particular relates to a system and method for improving the production stability of a tobacco shredded drying machine. Background technique [0002] my country is currently the world's largest tobacco producer and consumer. The total tax and profit achieved by the tobacco industry ranks first among all industries in the national economy. The development of the tobacco industry has made an important contribution to my country's economic growth. Cigarette production accounts for a relatively large proportion of tobacco production. Although the tobacco industry is a state-owned control industry, competition in the industry is still fierce due to the large number of cigarette companies in the industry. [0003] The cigarette production process is divided into three stages: silk making, crimping and packaging. Silk production is an important part of cigarette production, wh...

AI Technical Summary

Problems solved by technology

At present, most enterprises hope to analyze the entire production process through statistical process control (Statistical Process Control, SPC). Due to the limitations of methods and technologies, it is impossible to achieve accurate and scientific classification, resulting in the distortion of data results in SPC process analysis, and it is impossible to truly apply production process analysis and evaluation.

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