Multi-Objective Load Distribution Optimization for Hot Strip Mills

Jia, Shu-jin; Weigang, Li; Li, Xianghua; Du, Baigang

doi:10.1016/s1006-706x(13)60052-7

Cited by 16 publications

(7 citation statements)

References 3 publications

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“…A decision method based on weighted summation is generally used to select a compromise solution from the Pareto solution set. The objective function ( J ) of the weighted summation [ 25 ] can be defined as

J = \left(\alpha\right)_{1} \left(J^{'}\right)_{1} + \left(\alpha\right)_{2} \left(J^{'}\right)_{2} + \left(\alpha\right)_{3} \left(J^{'}\right)_{3}

where

\left(\alpha\right)_{1}

\left(\alpha\right)_{2}

, and

\left(\alpha\right)_{3}

are the weight coefficients of the three objective functions, respectively, and satisfy

\left(\alpha\right)_{1} + \left(\alpha\right)_{2} + \left(\alpha\right)_{3} = 1

\left(J^{'}\right)_{1}

\left(J^{'}\right)_{2}

, and

\left(J^{'}\right)_{3}

are dimensionless objective functions, which can be calculated using the z‐score method (Equation (15)).

$$\left(J^{'}\right)_{i} = \frac{J_{i} - \mu \left(\right.

…”

Section: Roll Profile Optimization Based On Dbscan and Nsga‐ii Algori...mentioning

confidence: 99%

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Optimization of Multi‐Segment Work Roll Profile for 1340 mm HC Tandem Cold‐Rolling Mills Based on DBSCAN and NSGA‐II Algorithms

Chen

Liang-gui

Pan

et al. 2023

steel research int.

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To address issues with saturated work roll bending force (WRB), maximum contact pressure between the work roll and intermediate roll (QWI), and challenging flatness lifting in a four‐stand, six‐high tandem cold mill with a 1340 mm width, the density‐based spatial clustering of applications with noise algorithm and the non‐dominated sorting genetic algorithm II are used for optimal design and online application research of a five‐segment work roll profile. When compared to a flat roll and a parabolic roll profile with a maximum crown of 15 μm, the optimized roll profile decreases the secondary crown of the roll gap (CW2) by 5.99 and 1.055 μm, respectively, and the fourth crown of the roll gap (CW4) by 0.21 and 0.39 μm, respectively. Additionally, QWI in the field of roll gap crown adjustment decreases by 1.04 and 0.445 kN mm−1. Industrial testing shows that the average integrated value of flatness in rolling the four extreme specifications of 1340 mm tandem cold‐rolling mills lowers by 2.65 IU following the application of the new roll profile, and the average reduction of WRB in the last stand is 2.215 MPa.

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J = \left(\alpha\right)_{1} \left(J^{'}\right)_{1} + \left(\alpha\right)_{2} \left(J^{'}\right)_{2} + \left(\alpha\right)_{3} \left(J^{'}\right)_{3}

where

\left(\alpha\right)_{1}

\left(\alpha\right)_{2}

, and

\left(\alpha\right)_{3}

are the weight coefficients of the three objective functions, respectively, and satisfy

\left(\alpha\right)_{1} + \left(\alpha\right)_{2} + \left(\alpha\right)_{3} = 1

\left(J^{'}\right)_{1}

\left(J^{'}\right)_{2}

, and

\left(J^{'}\right)_{3}

are dimensionless objective functions, which can be calculated using the z‐score method (Equation (15)).

$$\left(J^{'}\right)_{i} = \frac{J_{i} - \mu \left(\right.

…”

Section: Roll Profile Optimization Based On Dbscan and Nsga‐ii Algori...mentioning

confidence: 99%

“…A decision method based on weighted summation is generally used to select a compromise solution from the Pareto solution set. The objective function ( J) of the weighted summation [25] can be defined as…”

Section: Weighting Design For Multi-objective Optimizationmentioning

confidence: 99%

Optimization of Multi‐Segment Work Roll Profile for 1340 mm HC Tandem Cold‐Rolling Mills Based on DBSCAN and NSGA‐II Algorithms

Chen

Liang-gui

Pan

et al. 2023

steel research int.

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show abstract

“…After the Pareto optimal solution set is obtained, decisionmakers need to select a set of solutions as the final rolling schedule settings. The weighted-sum approach in [28] is used to select the trade-off solution which is shown as follows:…”

Section: Application On the Optimization Of Rolling Schedulementioning

confidence: 99%

Multi-Objective Optimization of Rolling Schedule for Five-Stand Tandem Cold Mill

Wang

Yin

et al. 2020

IEEE Access

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The optimization of rolling schedule is the main content of tandem cold rolling which will affect the quality of products directly. A rolling schedule with the objectives of minimum energy consumption, relative power margin and slippage preventing is established. First, in order to make the rolling schedule more accurate in the calculation process, a mathematical model combines with deep neural network is proposed to calculate the rolling force. Second, a multi-objective particle swarm optimizer with dynamic opposition-based learning is proposed to optimize the rolling schedule. It has a new particle learning strategy to update the moving position of particles. Moreover, opposition-based learning is proposed to make the particles jump out of local optima. Finally, the experiments are carried out based on the field data. Simulation results demonstrate that the accuracy of the rolling force is greatly improved. The proposed algorithm has a promising performance on both diversity and convergence. At the same time, the optimized rolling schedule can well balance the rolling power and prevent slipping between five stands comparing with the original rolling schedule. INDEX TERMS Multi-objective optimization, tandem cold rolling, deep neural network, rolling force, rolling schedule.

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“…However, in hot tandem rolling, the reduction ratio is determined by three key principles, namely, fully using of force (or torque) capacity of the stands, maximizing the production amount and minimizing rolling energy consumption. [26,27] It is difficult to modify much the reduction ratio for each stand to improve the flatness quality. The crown also influences the strip flatness significantly, therefore, in order to obtain good flatness quality, crown setup at exit of each stand is of great importance.…”

Section: Crown Setup For Hot Tandem Rollingmentioning

confidence: 99%

“…Reduction ratio of strip has a great influence on the transversal flow of metal and strip flatness. However, in hot tandem rolling, the reduction ratio is determined by three key principles, namely, fully using of force (or torque) capacity of the stands, maximizing the production amount and minimizing rolling energy consumption . It is difficult to modify much the reduction ratio for each stand to improve the flatness quality.…”

Section: Crown Setup For Hot Tandem Rollingmentioning

confidence: 99%

Flatness Analysis and Control of Strips with Different Thickness in 2250 mm Hot Tandem Rolling

Chai

Zhang

et al. 2018

steel research int.

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Aiming at the flatness difference between thick strip and thin strip under the same flatness control strategy on a 2250 mm hot tandem rolling line, a flatness calculation model is firstly established in this paper. With the unknown variable–transversal flow of metal solved by finite element methods, the flatness calculation model is used to analyze and compare the flatness and longitudinal residual stress evolution during thick strip and thin strip rolling. The result shows that under the premise of the constant exit relative crown in the downstream stands, the distribution of metal transversal flow due to larger reduction ratio in F2 and F3 stand causes the flatness of thin strip differing much from that of thick strip. In order to improve the flatness quality, a crown setup method is proposed. Based on the relationship among the distribution of metal transversal flow, entry relative crown, and the change of relative crown obtained from the finite element model, the exit crown of thin strip at each stand is optimized by genetic algorithm with a restriction of achieving the target crown at exit of F7 stand and a goal of good flatness quality during rolling.

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Multi-Objective Load Distribution Optimization for Hot Strip Mills

Cited by 16 publications

References 3 publications

Optimization of Multi‐Segment Work Roll Profile for 1340 mm HC Tandem Cold‐Rolling Mills Based on DBSCAN and NSGA‐II Algorithms

Optimization of Multi‐Segment Work Roll Profile for 1340 mm HC Tandem Cold‐Rolling Mills Based on DBSCAN and NSGA‐II Algorithms

Multi-Objective Optimization of Rolling Schedule for Five-Stand Tandem Cold Mill

Flatness Analysis and Control of Strips with Different Thickness in 2250 mm Hot Tandem Rolling

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