Rolling Line Contour Control Using Discrete Shape Variables
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Solution Overview
Problem
Existing rolling line control systems primarily focus on profile values, neglecting other discrete characteristic variables like edge values, dogbone values, edge drop values, and taper values, which can result in unsuitable contours for flat rolling materials, leading to financial losses and scrap materials.
Innovation Solution
The control system receives and adjusts multiple discrete characteristic variables defining the contour, including profile, edge, dogbone, edge drop, and taper values, allowing for precise control of the rolling process by capturing and comparing these variables during and after rolling, and optimizing control variables to align expected results with target specifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the control system focuses only on profile values, then the control system is simple, but the contour quality of the flat rolling material deteriorates
Solution Approach 1:
The control system segments the contour control into multiple independent discrete characteristic variables (profile value, edge value, dogbone value, edge drop value, taper value). Each variable is controlled separately with its own target value and control strategy, allowing comprehensive contour control while maintaining modular system architecture that doesn't excessively increase complexity.
Solution Approach 2:
The control system transitions from one-dimensional profile control to multi-dimensional contour control by incorporating five different discrete characteristic variables that describe different aspects of the contour (overall profile, edge thickness, dogbone effect, edge drop, and taper). This dimensional expansion enables comprehensive contour quality control without requiring a completely new control architecture.
2Manufacturing precision
If multiple discrete characteristic variables are controlled, then the contour quality improves, but the device complexity increases
Solution Approach 1:
The control system implements a universal control architecture that handles all five discrete characteristic variables (profile, edge, dogbone, edge drop, taper) through a common control framework. The same control logic, optimization algorithms, and actuator control mechanisms are reused across all variable types, achieving multi-functionality without proportionally increasing system complexity.
Solution Approach 2:
The control system merges the control of all five discrete characteristic variables into a unified control process. The target values for all variables are determined simultaneously using optimization algorithms that consider interactions between variables, and the control actions are coordinated through a single control system rather than separate independent control loops, reducing overall complexity.
3Ease of operation
If discrete characteristic variables are not controlled, then the control system is easier to operate, but the flat rolling material may become scrap
Solution Approach 1:
The control system implements self-service through automated determination of target values for all five discrete characteristic variables. The optimization algorithms automatically calculate appropriate target values based on the desired contour and material properties, eliminating the need for manual setting and reducing operational complexity while ensuring reliable product quality.
Solution Approach 2:
The control system incorporates feedback mechanisms that continuously monitor the actual contour characteristics and compare them with target values for all five discrete variables. This feedback enables automatic adjustment of control parameters to maintain product quality within specifications, reducing the need for manual intervention and ensuring high reliability of the rolling process.
Data Source
AI summary
Prior to the rolling of a flat rolling material (2) on a rolling line that includes a number of roll stands (1), a control system (3) receives actual variables (I) and target variables (Z) of the material (2). The control system (3) determines desired values (S*) for the roll stands (1), based on the actual (I) and target variables (Z) in combination with a model (10) of the rolling line, such that expected variables (E1) of the material (2) after its rolling are aligned as far as possible with the target variables (Z) and transfers the desired values (S*) to the roll stands (1) such that the material (2) is rolled according to the desired values (S*). The target variables (Z) comprise at least one freely selectable, discrete characteristic variable (K1 to K5, K2′ to K4′, K2″ to K4″) defining the contour (K) of the flat rolling material (2).