Thread making technological parameter dynamic quality stability characterization method

Abstract

Disclosed is a thread making technological parameter dynamic quality stability characterization method. The method comprises the steps that stable-state data and unstable-state data of a technological parameter in thread making procedures are collected; the deviation degree and the dispersion degree of the stable-state data and a technology index of the technological parameter are worked out according to the stable-state data; the unqualified time of the technological parameter is calculated according to the unstable-state data; the deviation degree and the dispersion degree of the technological parameter and the unqualified time of the unstable-state data are converted respectively according to a preset dynamic quality stability evaluation function in the stable-state process and a preset dynamic quality stability evaluation function in the unstable state process, and a dynamic quality stability assessed value of the stable-state data and a dynamic quality stability assessed value of the unstable-state data are of the technological parameter are acquired respectively; whether the dynamic quality stability assessed value of the stable-state data and the dynamic quality stability assessed value of the unstable-state data of the technological parameter reach corresponding preset threshold values respectively or not is judged, and if a dynamic quality stability assessed value does not each the preset threshold values, the executing process of the technological parameter is correspondingly adjusted, controlled and optimized. The thread making technological parameter dynamic quality stability characterization method achieves the optimized effect which is more comprehensive and is more in line with reality.

Description

technical field [0001] The invention relates to a technique for controlling and optimizing technical parameters of shredded cigarettes, in particular to a method for improving the control effect of technical parameters of shredded shreds. Background technique [0002] In the cigarette processing industry, shredded processing is a very important process, and its treatment effect directly affects the intrinsic quality of tobacco. Therefore, it is necessary to optimize the control of shredded processing parameters to improve the quality and stability of shredded finished products. The control level of key processes and key parameters of silk production line is usually characterized by quality evaluation. Quality evaluation must truly and objectively reflect the quality of each key process and key parameters in order to provide a basis for continuous quality improvement and management assessment. [0003] In the production process of the silk production line, the control stage o...

AI Technical Summary

Problems solved by technology

At present, there are the following limitations in the quality evaluation of the key process and key parameters of the silk production line: ① The production process objects covered by the key process evaluation are not comprehensive

② Existing evaluation methods have certain limitations

On the one hand, whether it is the Cpk (or CP) of SPC or the SIGMA level, the statistical calculation is based on the assumption that the data conforms to the normal distribution. However, for the cigarette production process, there are many external factors, such as changes in environmental temperature and humidity. , the unevenness of the tobacco leaf itself, etc., the process data cannot fully satisfy the normal distribution; on the other hand, there are certain defects in the use of Cpk evaluation in SPC. ③ There are deficiencies in the application of evaluation methods in guiding process dynamic quality control. Although DPk (dynamic Cpk) has recently been proposed to characterize the operation of production process procedures or parameters in real time, how to guide operators in the error zone of DPK has not yet been established. Intuitive implementation method, while the SIGMA level belongs to post-event verification, and cannot dynamically guide production quality control

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