Construction Project of Automatic Control System for Expanded Tobacco Stem Rejection at Wuhan Cigarette Factory, Hubei China Tobacco

Project Background

To automatically remove stems from expanded tobacco, a cigarette factory implemented intelligent technologies and applications for the pneumatic separation process of expanded tobacco.

Requirements

• Ability to process diverse data types and integrate with upper-layer applications, supporting multidimensional data processing and common star and snowflake schemas;

• Standardized query interfaces with scalability and growth potential;

• Technology aligns with current big data trends and demonstrates forward-looking capability;

• Data capacity: Supports massive volumes of data;

• Scalability: Supports online horizontal scaling and ultra-large clusters;

• Processing capability: Complete complex job processing within 3 hours per day;

• I/O performance: High data compression and parallel loading;

• High availability: 24/7 uninterrupted service with backup and disaster recovery capabilities, ensuring no data loss due to failures;

• Hardware environment: Supports x86 architecture and Linux;

• SQL support: Standardized and unified, compliant with SQL92, and supporting JDBC and ODBC interfaces.

The project deployed GBase 8a MPP Cluster V9 on a single node to meet system data analysis requirements, in conjunction with built-in sensors and a custom-developed Modbus data interface to collect data. System Architecture Diagram

Figure 1: System Architecture Diagram

To achieve intelligent and precise quality control adjustments, the system established data models and data-driven guidance. Based on data affecting the existing stem rejection rate, the following key parameters are collected:

• Primary air separation: air speed, temperature and humidity in the separation chamber;

• Secondary air separation: air speed, cut tobacco flow rate, temperature and humidity in the duct;

• Others: stem mass, damper opening information, VFD frequency, high-speed belt motor current, cut tobacco moisture and temperature, etc.

By leveraging the linear relationship between gas-phase pressure energy loss and different cut tobacco mass flow rates during conveying, fundamental data for measuring tobacco mass flow is established. Combined with fluid flow similarity theory and the gas-solid coupling flow patterns in tobacco conveying, this enables refined measurement range subdivision and improved measurement accuracy. Stable data is obtained through computerized calculations.

• After project deployment, the following technical indicators have been achieved: purity of expanded tobacco after pneumatic separation ≥99.5%, and qualified tobacco in rejected material ≤15% of total rejected material.

• Leveraging data warehouse technology, a comprehensive data management architecture was designed to transform scattered data from various equipment sensors into centralized, accessible, accurate, and actionable information resources.

• A unified data and information access platform was established to enable enterprise-level statistical analysis and information dissemination.

• A unified metrics and dimensions system was set up to ensure the uniqueness of data algorithms and the correctness of statistics.

• Data relationships were established, including associations between data items and between different process stages, providing complete and reliable data and analytics support for subsequent intelligent control.