| 摘要: |
| 目的 为了解决卷烟卷制过程控制精度低、质量波动大等问题，建立一种卷烟卷制质量的整合控制模式。方法 采用累计和方法预测重量和圆周质量特性的偏差，并进行在线调整;同时以质量和圆周的标偏为目标函数，以吸阻均值为约束条件，基于二次响应曲面建立卷制工艺参数的多目标优化设计，由此建立这两方面相结合的质量控制模式，并采用自学习优化和遗传算法对模型进行优化设计。结果 选取漯河卷烟厂ZJ19卷接机对某一牌号卷烟的卷制过程进行在线应用分析和验证，结果表明:烟支质量、圆周、吸阻等卷制质量指标的均值与目标值的偏差分别降低了66.6%、86.7%、65.6%，标准偏差分别降低了31.8%、65.2%、11.9%。结论 这种偏差预测调整和多目标参数优化相结合的质量控制模式能够有效提升卷制过程的综合质量水平。 |
| 关键词: 卷制质量 累计和 预测调整 响应曲面 多目标优化 |
| DOI：10.19554/j.cnki.1001-3563.2023.15.028 |
| 分类号:TS206.4 |
| 基金项目:国家自然科学基金项目(71672209);河南中烟工业有限责任公司科技项目(AW202133) |
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| Integrated Control of Cigarette Manufacturing Quality Based on Deviation Forecast and Parameter Optimization |
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HAN Li-qiang1, LIU Xin-xian1, WANG Zhi-yong1, WANG Hai-yu2, WANG Yan3
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(1. Luohe Cigarette Factory, China Tobacco Henan Industrial Co., Ltd., Henan Luohe 462003, China;2. Business School, Zhengzhou University, Zhengzhou 450001, China;3. Guangzhou Rongzhi Technology Co., Ltd., Guangzhou 510220, China)
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| Abstract: |
| The work aims to develop an integrated control mode of cigarette manufacturing quality to solve the low control accuracy, large quality variation and other problems in cigarette manufacturing. The cumulative sum method was used to predict the deviation of weight and circumference quality characteristics and adjust online. At the same time, with the standard deviation of circumference and weight as the objective function and the mean of draw resistance as the constraint condition, the multi-objective optimization design of process parameters was established based on the quadratic response surface, and the quality control mode of cigarette manufacturing quality combining these two aspects was established, and self-learning optimization and genetic algorithm were used to optimize the model. The ZJ19 cigarette making machine of Luohe Cigarette Factory was selected for online application analysis and verification of the cigarette manufacturing process of a certain brand. The results showed that the deviation between the average value of cigarette weight, circumference, draw resistance and the target value was reduced by 66.6%, 86.7%, 65.6% respectively, and the standard deviation was reduced by 31.8%, 65.2%, 11.9% respectively. This quality control mode combining deviation prediction adjustment and multi-objective parameter optimization can effectively improve the comprehensive quality level of the cigarette making process. |
| Key words: cigarette manufacturing quality cumulative sum forecast adjustment response surface multi-objective optimization |
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