Continuous Casting Planning With Strand Image Re-Scheduling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current production planning systems in continuous casting plants lack dynamic response to production events, leading to increased costs, storage, and scrap due to deviations in process conditions, quality, and product dimensions, with limited ability to adjust production plans during the process.
Innovation Solution
A method involving real-time comparison of setpoint and actual production parameters to create a strand image, allowing for dynamic adjustment of production plans by a production planning system, using a decoupled bi-directional connection to maintain continuous production while optimizing for maximum sales revenue and minimizing storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a predefined production plan is used without dynamic adjustment, then production stability is maintained, but the system cannot respond to process events, quality deviations, or product dimension variations, leading to increased scrap, storage costs, and production losses
Solution Approach 1:
The production planning system transitions from a static predefined plan to a dynamic system that continuously monitors actual production parameters (strand temperature, casting speed, mold level) and automatically adjusts the production plan in real-time. This enables the system to adapt to process events, quality deviations, and product dimension variations without manual intervention, resolving the contradiction between adaptability and system complexity by making the complexity manageable through automated dynamic adjustments.
Solution Approach 2:
The system implements continuous feedback loops where actual production parameters are measured and compared against the production plan. When deviations are detected (such as quality issues or dimension variations), the system automatically feeds this information back to adjust the production plan, creating a closed-loop control system that responds dynamically to production events while maintaining operational stability.
2Loss of time
If the production plan is adjusted after deviations occur, then response to production events is delayed, but real-time adjustment increases system complexity and computational load
Solution Approach 1:
The system performs preliminary actions by continuously monitoring production parameters and predicting potential deviations before they occur. The production planning system is prepared in advance with multiple contingency plans and can switch to alternative plans proactively when deviations are detected, rather than reacting after the fact. This reduces response time by being prepared beforehand while managing complexity through pre-computed alternative scenarios.
Solution Approach 2:
The system enables dynamic real-time adjustment of the production plan by continuously updating cutting positions, product specifications, and production parameters based on current production conditions. This dynamic capability allows immediate response to deviations without requiring complex manual re-planning, as the system automatically recalculates and implements optimal adjustments in real-time.
3Productivity
If standard cutting plans are used without optimization, then production simplicity is maintained, but product yield is reduced and storage costs increase due to inability to accommodate deviations
Solution Approach 1:
The system optimizes product yield by dynamically changing critical parameters such as cutting positions, product lengths, and specifications based on actual production conditions. When deviations occur, the system recalculates optimal cutting patterns to maximize usable product from the strand, converting what would be scrap into sellable products. This parameter optimization increases productivity and reduces storage costs while the automated nature of the system keeps the complexity manageable.
Data Source
AI summary
A dynamic production planning method for a continuous casting plant for casting a strand with a production system which has a predefined production plan, which method includes comparing target production parameters with actual production parameters. If the actual production parameters deviate from the target production parameters, a strand image is created on the basis of actual production parameters. With the aid of the calculated strand image, a check is carried out within the predefined production plan and, if possible, a new production plan is created. If no solution can be found from the predefined production plan, the strand image is transmitted to a production planning system. The production planning system creates a new production plan from all available orders on the basis of a predefined optimization criterion. The new production plan is subsequently transmitted to the production system.