Hot Rolling Slab Scheduling via 2D Grid Graph Optimization
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Solution Overview
Problem
Conventional techniques do not provide a rational method for determining the combined sequence of direct and inventory slab sequences in hot rolling processes, leading to inefficient scheduling and reliance on manual trial-and-error methods.
Innovation Solution
A two-dimensional grid graph is created with direct and inventory slab sequences as dimensions, where nodes represent slabs with attributes like width, thickness, and processing time, and edges are weighted based on connectivity, idle time, and wait time, allowing for the calculation of a combined sequence as a shortest path search problem using algorithms like Dijkstra's.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual trial-and-error methods are used to determine the combined sequence of direct and inventory slabs, then scheduling flexibility is maintained, but scheduling efficiency and productivity deteriorate
Solution Approach 1:
The patent replaces manual trial-and-error scheduling methods with an automated computer-based system that uses integer programming algorithms to determine the optimal combined sequence of direct and inventory slabs. This substitution of mechanical/manual operations with automated computational methods directly improves scheduling efficiency while managing system complexity through software implementation.
Solution Approach 2:
The patent transforms the scheduling problem into a mathematical optimization problem by defining objective functions and constraints based on various parameters such as slab characteristics, heating requirements, and rolling constraints. By changing the approach from qualitative manual adjustment to quantitative parameter-based optimization, the system achieves higher productivity through automated decision-making.
2Manufacturing precision
If separate scheduling of direct and inventory slabs is performed, then individual sequence optimization is achieved, but combined sequence optimization deteriorates
Solution Approach 1:
The patent merges the separate scheduling of direct slabs and inventory slabs into a unified combined sequence determination process. By integrating both slab types into a single optimization model that considers their interactions and constraints together, the system achieves superior overall sequence optimization that accounts for the combined effects on heating furnace utilization and rolling mill productivity.
3Ease of manufacture
If conventional scheduling methods are used, then implementation simplicity is maintained, but scheduling rationality and optimization deteriorate
Solution Approach 1:
The patent introduces a computer-based scheduling system as an intermediary between the complex optimization requirements and the final scheduling output. This intermediary handles the sophisticated integer programming calculations and constraint satisfaction automatically, providing rational and optimized schedules without requiring users to directly implement complex algorithms, thus maintaining ease of use while improving scheduling quality.
Data Source
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AI summary
[Object] To solve combined scheduling of two different slab sequences by a rational technique. [Solution] A two-dimensional grid graph having a direct slab sequence as a first dimension and an inventory slab sequence as a second dimension is prepared by processing of a computer as a data structure represented on a memory or a hard disk drive of the computer. A processing program of the computer generates two child nodes corresponding to a direct slab and an inventory slab, in each node of the two-dimensional graph according to a predetermined algorithm. By defining an appropriate weighting function, the processing program of the computer weights edges between nodes in the two-dimensional grid graph. After forming the weighted graph on a storage device of the computer such as the memory or the hard disk drive, the processing program of the computer calculates a path from a start point to an end point as a shortest path search problem such as known Dijkstra's algorithm.