Cloud-Edge Alumina Production Control for Real-Time Energy Optimization
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Solution Overview
Problem
Traditional aluminum oxide production processes face challenges with poor raw material quality, high energy consumption, and insufficient product quality due to suboptimal control indexes set by experience-based knowledge workers, and difficulties in integrating data across production procedures to achieve overall process optimization.
Innovation Solution
An aluminum oxide production operation optimization system based on cloud-edge collaboration, which includes a process data acquisition unit, cloud storage and collaboration optimization calculating unit, local collaboration production operation optimization control unit, and data transmission unit, enabling data preprocessing, real-time analysis, and strategic optimization across the production process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If control indexes are set by experience-based knowledge workers, then operational simplicity is maintained, but production optimization is insufficient leading to high energy consumption
Solution Approach 1:
The patent introduces an optimization system comprising data acquisition modules, analysis modules, and control modules as intermediaries between the production process and operators. These modules collect process data, analyze it using predetermined algorithms, and generate optimization recommendations, thereby reducing energy consumption without requiring operators to have extensive expertise while maintaining system manageability
Solution Approach 2:
The system enables self-service optimization by automatically collecting process data from various production stages, analyzing it through predetermined algorithms, and generating control parameter recommendations without continuous human intervention. The system serves itself by autonomously identifying optimization opportunities and implementing control adjustments
2Productivity
If data integration across working procedures is implemented, then overall process optimization is achieved, but system complexity increases
Solution Approach 1:
The patent segments the production process into distinct working procedures (raw material preparation, sintering, crushing, screening) with dedicated data acquisition modules for each segment. This segmentation allows data to be collected and analyzed at appropriate granularities while maintaining overall process integration, enabling productivity improvement without overwhelming system complexity
Solution Approach 2:
The optimization system employs universal modules that can handle multiple functions: data acquisition modules collect data from various sources, analysis modules process different types of process data using similar algorithms, and control modules implement optimizations across different production stages. This multi-functionality reduces overall system complexity while achieving comprehensive process optimization
3Productivity
If real-time data analysis and optimization control are implemented, then production efficiency improves, but energy consumption for data processing increases
Solution Approach 1:
The system implements partial real-time analysis by continuously monitoring key process parameters that have the greatest impact on energy consumption and productivity, while using less frequent analysis for secondary parameters. This selective real-time approach improves production efficiency through targeted optimizations while minimizing the energy required for comprehensive data processing
Data Source
AI summary
Provided is an aluminum oxide production operation optimization system and method based on a cloud-edge collaboration, which relates to the technical field of an aluminum oxide production operation optimization. According to the system and method, firstly the whole-flow data in the aluminum oxide production process is acquired, the data is pre-processed, then the pre-processed data is transmitted to a local collaboration production operation optimization unit, the local collaboration production operation optimization unit firstly judges working conditions for the current aluminum oxide production process, an optimization strategy needing to be operated at present is automatically switched according to the working condition, and the local operation optimization strategy obtains the actual setting value of the aluminum oxide production operation indexes.