基于大数据的卷烟制造过程参数智能优化研究

Intelligent Optimization of Cigarette Manufacturing Process Parameters Based on Big Data

烟草工业企业从发展信息化建设以来,已积累了丰富的经验,更重要的是已形成了相当规模的大数据资产。但由于企业内部生产自动化水平不高,各应用系统之间存在信息壁垒,且缺乏实施智能制造的技术资源,导致制造过程难以摆脱人为干预,数据价值无法被充分发挥。为支撑企业具备大数据分析挖掘能力,加速企业智能化升级,提出由感知与控制层、数据存储层、数据计算层、数据应用层四个层次和一个消息总线平台构成的大数据分析平台技术体系架构。针对大数据驱动的制造过程参数智能优化技术进行实践探讨,为烟草工业企业实现智慧工厂目标提供参考。

Tobacco industry enterprises have accumulated rich experience since developing informatization construction,and more importantly,they have formed large-scale big data assets. However,due to the low level of production automation within the enterprise,the existence of information barriers between various application systems,and the lack of technical resources to implement intelligent manufacturing,it is difficult to get rid of human intervention in the manufacturing process,and the value of data cannot be fully utilized.In order to support the enterprise’s ability to mine big data and accelerate enterprise intelligent upgrade,this paper proposes a big data analysis platform technology consisting of four layers:perception and control layer,data storage layer,data calculation layer,data application layer and a message bus platform.Finally,a practical discussion is made on the dynamic optimization technology of manufacturing parameters driven by big data,which provides a reference for tobacco industry enterprises to achieve the goal of smart factories.