Production System Digital Modeling for Complex Process Flow Simulation
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Solution Overview
Problem
Current metallurgical process simulation methods are inadequate for complex nonferrous metallurgical processes, leading to inefficiencies, bottlenecks, and failures in production systems due to insufficient system flow design and simulation.
Innovation Solution
A method and apparatus for modeling a digital model of a production system, involving dividing process flows into units, determining process relationships, and constructing digital models of architecture, flow, and environment to optimize system flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simple metallurgical process simulation methods are used, then the simulation process is easy to implement, but the system cannot simulate complex production systems leading to production failures
Solution Approach 1:
The patent divides the complex production system into multiple process units (e.g., mixing unit, reaction unit, separation unit) that can be independently modeled and simulated. Each unit has its own digital model representing specific functions, allowing complex systems to be broken down into manageable components while maintaining overall system accuracy.
Solution Approach 2:
The patent introduces a multi-dimensional modeling approach by creating digital models that encompass not only physical processes but also information flow, energy flow, and material flow dimensions. This enables comprehensive simulation of complex production systems by adding informational and control dimensions to traditional process modeling.
2Productivity
If process units are modeled in detail, then system flow optimization is improved, but the modeling complexity increases
Solution Approach 1:
The patent creates a universal digital model framework that can represent multiple process units with different functions using a common modeling structure. The model architecture supports various unit operations (mixing, reaction, separation, heating) through standardized components, reducing modeling complexity while enabling detailed system flow optimization across diverse process units.
Solution Approach 2:
The patent performs preliminary system flow design and simulation using the digital model before actual production implementation. By simulating different flow configurations and identifying bottlenecks in advance, the system optimizes productivity without requiring complex real-time adjustments during production.
3Measurement precision
If comprehensive flow data is collected for all process units, then simulation accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent extracts and focuses on key flow data parameters that are most critical for system flow optimization, rather than processing all available data. The digital model identifies and prioritizes essential measurements (material flow rates, energy consumption, information signals) while filtering out redundant data, reducing processing complexity while maintaining simulation accuracy.
Solution Approach 2:
The patent introduces an information flow layer that acts as an intermediary between physical process data and simulation models. This information layer standardizes and structures flow data from multiple process units, enabling accurate simulation without directly handling the full complexity of raw data from all sensors and measurement points.
Data Source
AI summary
The present disclosure provides a method and an apparatus for modeling a digital model of a production system, wherein the method comprises: dividing a process flow of the production system according to the process to obtain a plurality of process units to be constructed and link units; determining the process relationship between the process units, and constructing a digital model architecture, a flow model and an environment model; and constructing a digital model corresponding to the system flow according to the digital model architecture, the flow model and the external environment. With the solution of the present disclosure, it is able to realize the modeling of the process flow for complex production systems and improve the process control efficiency of the production system.