Air Compressor Parameter Recommendation for Energy-Saving Control
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Solution Overview
Problem
Current factory control systems lack the ability to provide equipment managers with suggestions on equipment parameter settings for air compressors, making it difficult to optimize energy efficiency and reduce electricity waste, as they rely on subjective experiences rather than data-driven insights.
Innovation Solution
An equipment parameter recommendation method that generates feature variables from air compressor operation data, uses a production prediction model to calculate a predicted total displacement volume, and determines suggested equipment parameters to optimize energy usage, which are then displayed for adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If equipment managers manually inspect and adjust equipment parameters based on subjective experience, then they can make decisions without complex systems, but energy efficiency optimization is insufficient and electricity waste occurs
Solution Approach 1:
The patent introduces an equipment parameter recommendation system as an intermediary between the existing group control system and equipment managers. This system includes a model training unit that creates prediction models, a recommendation unit that generates parameter suggestions, and provides data-driven recommendations to managers, reducing energy waste without requiring managers to directly handle complex analytical systems
Solution Approach 2:
The system enables self-service by automatically collecting equipment operation data, training prediction models, and generating parameter recommendations without requiring manual inspection or complex human analysis. The equipment manager simply receives ready-to-use recommendations, allowing the system to serve itself in optimizing energy efficiency
2Manufacturing precision
If professionals conduct status inspections on each equipment to determine parameters, then accurate parameter settings can be achieved, but time consumption increases and productivity decreases
Solution Approach 1:
The patent replaces the mechanical inspection process with an automated information processing system. The model training unit creates prediction models that automatically analyze equipment data, and the recommendation unit generates parameter suggestions, substituting manual professional inspection with automated computational analysis to maintain accuracy while improving productivity
Solution Approach 2:
The system performs preliminary action by pre-training prediction models with historical equipment data before actual parameter determination is needed. The model training unit prepares the prediction models in advance, so when parameter recommendations are needed, the system can quickly generate accurate suggestions without requiring time-consuming manual inspections
3Device complexity
If equipment parameters are adjusted based on long-term accumulated personal subjective experiences, then no complex prediction models are needed, but energy saving optimization is limited and cannot meet manufacturing needs
Solution Approach 1:
The patent applies parameter changes by using prediction models to analyze equipment operation parameters and determine optimal settings. The recommendation unit generates specific parameter adjustments based on data-driven insights, enabling energy saving optimization that goes beyond subjective experience while managing model complexity through practical implementation
Data Source
AI summary
The disclosure provides an equipment parameter recommendation method, an electronic device and a non-transitory computer readable recording medium. Multiple feature variables associated with multiple air compressors are obtained according to equipment operation information of each of the air compressors. A predicted total displacement volume is obtained according to multiple feature variables associated with the air compressors and a production prediction model. A suggested equipment parameter of at least one of the air compressors is determined according to the predicted total displacement volume and an estimated maximum loading volume associated with the air compressors. Suggestion information associated with the suggested equipment parameter is displayed via the display.