Cross-Process Excess Steel Matching Using Weighted Bipartite Graphs
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Solution Overview
Problem
The existing methods for using cold/hot-rolled excess materials in steel production are inefficient and prone to errors due to reliance on artificial experience, making it difficult to achieve global optimization and automate the cross-process use of these materials.
Innovation Solution
A method and device that utilize a weighted binary graph and the maximum weight matching algorithm to automatically match cold/hot-rolled excess materials with futures contracts, optimizing the use of excess materials by determining the maximum sum of matching weights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If artificial experience-based methods are used to match cold/hot-rolled excess materials with futures contracts, then the implementation process is simple to understand, but the work efficiency is low and mistakes are made easily
Solution Approach 1:
The patent replaces the manual artificial experience-based matching process with an automated computer system that uses graph theory algorithms. The system automatically constructs weighted binary graphs, calculates matching weights based on multiple criteria (material properties, contract requirements, process compatibility), and determines optimal matching schemes, thereby eliminating human errors and significantly improving work efficiency while maintaining implementation feasibility through standardized algorithms
Solution Approach 2:
The system enables self-service automation where the computer automatically performs material-contrat matching without human intervention. The algorithm independently evaluates multiple matching criteria, computes optimal pairings, and generates executable matching schemes, allowing the system to serve itself in the matching process while improving productivity and reducing manual labor
2Productivity
If artificial experience-based methods are used for material matching, then the system is easy to implement, but global optimization is difficult to achieve
Solution Approach 1:
The patent introduces a multi-dimensional evaluation framework by constructing weighted binary graphs that consider multiple criteria simultaneously (material properties, contract requirements, process compatibility, timing constraints). This transforms the simple one-dimensional matching into a multi-dimensional optimization problem, enabling global optimization across all constraints while using systematic graph theory methods to manage the increased complexity
Solution Approach 2:
The system dynamically adjusts matching weights as parameters based on different criteria (material grade compatibility, process sequence alignment, contract priority, timing constraints). By changing and optimizing these weight parameters, the system achieves global optimization of the matching scheme, considering all relevant factors rather than relying on fixed artificial rules
3Reliability
If automated matching systems are implemented, then work efficiency and accuracy are improved, but the system complexity increases
Solution Approach 1:
The patent replaces error-prone manual matching with automated computer-based graph algorithms that ensure consistent and accurate evaluation of all matching criteria. The systematic calculation of matching weights and optimal pairings eliminates human errors, improving reliability and matching accuracy while using well-established graph theory methods to manage system complexity
4Loss of time
If manual matching processes are used, then the system is simple to operate, but the production cycle of futures contracts is extended
Solution Approach 1:
The automated system enables continuous operation of the material matching process, eliminating interruptions and delays associated with manual review and decision-making. The algorithm continuously evaluates available excess materials against futures contract requirements and immediately generates optimal matching schemes, significantly reducing the production cycle time while maintaining operational simplicity through automated decision-making
Data Source
AI summary
This disclosure relates to the field of metallurgical automation technologies, and discloses a method and device for cross-process use of cold/hot-rolled excess material, medium, and program product. The method is applied in an electronic device. In this method, multiple futures contracts and multiple cold/hot-rolled excess materials with same steel grade are obtained, forming at least one matching pair consisting of a futures contract and a cold/hot-rolled excess material by taking the multiple futures contracts and the multiple cold/hot-rolled excess materials as nodes in a weighted binary graph, to construct a matching relationship graph. In addition, a matching weight of each matching pair in the at least one matching pair is determined. Then, a use solution is obtained by computing the matching relationship graph based on a binary graph maximum weight matching algorithm. By doing so, the automation and scale of cross-process use of cold/hot-rolled excess materials can be implemented, the use efficiency of cold/hot-rolled excess materials and futures contract can be improved, and the optimal use of excess materials can be achieved.