Surplus Slab Assignment Optimization in Steel Hot Rolling
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Solution Overview
Problem
The iron and steel industry faces challenges in efficiently assigning surplus slabs to orders due to manual assignment methods that fail to consider various constraints, leading to high cut-loss, inventory costs, and wastage of resources.
Innovation Solution
A method and device using a mathematical model with a mixed scatter search algorithm to optimize the assignment of surplus slabs to orders based on steel grade, width, length, weight, and due dates, ensuring comprehensive and reasonable matching, reducing surplus inventory and thermal loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual assignment method is used for surplus slabs, then operation simplicity is maintained, but assignment accuracy and resource utilization deteriorate
Solution Approach 1:
The patent replaces the manual mechanical assignment system with an automated computer-based optimization system. The system uses algorithms to automatically match surplus slabs with orders based on multiple constraints (steel grade, dimensions, weight, due dates), substituting human manual operations with computational processing to achieve both automation and high assignment accuracy.
2Productivity
If comprehensive constraints are considered in assignment, then resource utilization improves, but computational complexity increases
Solution Approach 1:
The patent segments the complex assignment problem into manageable components by categorizing constraints into different dimensions (steel grade compatibility, dimensional matching, weight constraints, temporal requirements). The system processes each constraint category separately through structured algorithms, making the overall complex problem solvable while maintaining comprehensive constraint consideration.
Solution Approach 2:
The patent transforms the assignment problem from a qualitative manual process into a quantitative optimization problem by defining specific parameters for each constraint (e.g., steel grade thresholds, dimensional tolerances, weight ranges, due date priorities). This parameterization enables systematic computational processing while maintaining flexibility in handling diverse constraints.
3Adaptability or versatility
If surplus slabs are stored in yard, then production flexibility is maintained, but inventory costs and resource occupation increase
Solution Approach 1:
The patent implements preliminary assignment of surplus slabs to specific orders before hot rolling based on predicted demand and current inventory. By proactively matching surplus slabs with potential orders using optimization algorithms, the system reduces the need for large surplus inventory storage while maintaining production flexibility to respond to actual customer demands.
Data Source
AI summary
A method for assigning surplus slabs in slab yards to orders includes loading slab pre-yards of a plurality of production lines with surplus slabs, describing the assignment of the surplus slabs to the orders with a mathematical model, grouping order data and slab data based on steel grades, obtaining an assignment scheme for the surplus slabs and the orders in each group with a mixed scatter search algorithm, and assigning the surplus slabs to the orders using the assignment scheme. If a surplus slab is in a pre-yard of a production line associated with an order the surplus slab is assigned to, the slab is moved using a crane to the production line. Otherwise, the slab is moved to the pre-yard associated with the production line, and then moved using a crane to the production line. The slab is then heated and rolled by the production line.