项目基于设备自身监测技术的应用和发展,以信息系统为支撑,运用大数据理论对关键流程设备的状态信息(运行参数、工艺质量、过程记录等)进行获取、筛选、分类、处理和利用,并开发数据图形化工具全方位、多维度直观、快捷监控设备的实时状态和变化趋势。文章对烟草生产设备状态精确管控模式进行了探索。 Based on the application and development of the self-monitoring technology of the equipment, the project uses the big data theory to obtain, filter, classify, process and utilize the status information (operating parameters, process quality, process records, etc.) of the key process equipment based on the information system. And the development of data graphical tools comprehensive, multi-dimensional visualization, quick monitoring of real-time equipment status and trends. The paper explores the precise control of tobacco production equipment status mode.