Fine tuning straightening process using genetic algorithms and finite element methods

Pernía, A.; Martínez-de-Pisón, Francisco Javier; Ordieres, J.; Alba, Fernández; Blanco‐Fernández, Julio

doi:10.1179/030192309x12549935902301

Cited by 15 publications

(10 citation statements)

References 15 publications

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“…To determine the roll positions leading to a flat product Pernía et al [11] introduced an approach employing genetic algorithms for optimising the process parameters. As the optimisation by such genetic algorithms requires a large number of simulation runs, a different approach is the use of feedback control-loops within an FE code.…”

Section: State Of the Artmentioning

confidence: 99%

Numerical Investigation of a Process Control for the Roller Levelling Process Based on a Force Measurement

Grüber

2016

MSF

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When processing conventional semi-finished metal strips, distinctive changes in the material properties along the strip length are unavoidable. The roller levelling process is sensitive to changes of those strip characteristics. Thus, a process control allowing for an online adaption of the roller levelling machine according to the actual strip characteristics is highly desirable. In order to enable a precise process layout, the calculation by the Finite Element Method (FEM) provides a suited strategy. Furthermore, the coupling of user-subroutines to an FE code offers the possibility to implement and test respective control strategies. This work proposes a control strategy that is based on a force measurement in the first load triangle of a levelling machine. A first FE model including a feedback control is used to calculate the dependence between the force in the first load triangle and the roll intermesh in the last load triangle leading to a flat sheet. The results are transferred to meta models – so called control curves – that give a direct relationship between the measured force and the roll intermesh. Within a second FE setup a feed-forward control based on these control curves is implemented and the proposed control strategy is investigated for varying yield strengths along the strip length. Thus, the time consuming FE simulations that are necessary to obtain the control curves are decoupled from the actual levelling process. According to the obtained results, the introduced approach is able to improve the sheet flatness for thin sheets when a change in the material properties occurs.

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Section: State Of the Artmentioning

confidence: 99%

Numerical Investigation of a Process Control for the Roller Levelling Process Based on a Force Measurement

Grüber

2016

MSF

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“…These numerical investigations are used to identify a suitable set up of the straightening roll infeed and the state of stress within the material [5][6][7][8]. But not only numerical calculations are expedient, analytical models can help as well to provide information concerning the infeed of the straightening rolls, as shown in [9][10][11][12].…”

Section: Intr Introduction Oductionmentioning

confidence: 99%

Innovative Measurement Of Stress Superposed Steel Strip For Straightening Machines

Bader¹,

Bathelt²,

Djakow³

et al. 2021

Esaform 2021

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Higher quality requirements by customers demand higher precision and accuracy from manufacturing processes. Application oriented preparation of semi-finished materials is key for subsequent forming operations, therefore, straightening machines are employed. Straightening strengthens the material by increasing plastic deformation by means of strain hardening, resulting in undesirable reduction in formability when processing high strength materials, in particular. Conventional roll-type straightening machines process either bars or strips. This is achieved upon passing material between rolls arranged in two staggered rows. However, conventional straightening processes do not adapt to the local varying distortion of coiled strips. Innovative, self-correcting process control techniques, which adapt to the initial geometric characteristics of the strip, present a promising approach to fix this issue through optimization of the leveling process. Here, an innovative strategy to improve straightening of high strength steel materials (1.4310) is presented. This implements optimized leveling, adding minimal plastic deformation and, thus, strain hardening. To operate an intelligent straightening machine, a reliable online measurement of the surface defects is fundamentally essential. The MagnaTest, which is developed for material testing, is made feasible for such purposes after calibrating for curvature measurement. Preliminary results are promising in regards to measuring the curvature online, so that the following straightening process can be close loop controlled. The bending measurement is linked to open/closed loop control, therefore providing an optimal straightening result in regards to formability, leveling, and reduced strain hardening.

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“…LG15.5 × 14.5 × 400 Distance between two clamps ( s L 2 /mm) 300 Initial deflection ( δ 0 /mm) 1.581 Most of research on the simulation of straightening processes generally applied concentrated force on the workpiece [8,9,14,16]. However, it is difficult to accurately control the force in the actual straightening process.…”

Section: Finite Element (Fe) Simulation Of the Multi-step Straightenimentioning

confidence: 99%

“…The straightening process is actually continuous and it is a multi-step deformation process based on the classical elasto-plastic theory. The residual stress generated by the previous straightening process would influence the loading stress of the following process due to stress superposition, and the straightening properties of workpiece are also influenced [8,9]. Therefore, it is imperative to establish a more accurate predictive model of straightening stroke considering the stress superposition of different straightening procedures.…”

Section: Introductionmentioning

confidence: 99%

Analytical Model of a Multi-Step Straightening Process for Linear Guideways Considering Neutral Axis Deviation

et al. 2018

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Abstract:The cross-sectional shape of a linear guideway has been processed before the straightening process. The cross-section features influence not only the position of the neutral axis, but also the applied and residual stresses along the longitudinal direction, especially in a multi-step straightening process. This paper aims to present an analytical model based on elasto-plastic theory and three-point reverse bending theory to predict straightening stroke and longitudinal stress distribution during the multi-step straightening process of linear guideways. The deviation of the neutral axis is first analyzed considering the asymmetrical features of the cross-section. Owing to the cyclic loading during the multi-step straightening process, the longitudinal stress curves are then calculated using the linear superposition of stresses. Based on the cross-section features and the superposition of stresses, the bending moment is corrected to improve the predictive accuracy of the multi-step straightening process. Finite element analysis, as well as straightening experiments, have been performed to verify the applicability of the analytical model. The proposed approach can be implemented in the multi-step straightening process of linear guideways with similar cross-sectional shape to improve the straightening accuracy.

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Fine tuning straightening process using genetic algorithms and finite element methods

Cited by 15 publications

References 15 publications

Numerical Investigation of a Process Control for the Roller Levelling Process Based on a Force Measurement

Numerical Investigation of a Process Control for the Roller Levelling Process Based on a Force Measurement

Innovative Measurement Of Stress Superposed Steel Strip For Straightening Machines

Analytical Model of a Multi-Step Straightening Process for Linear Guideways Considering Neutral Axis Deviation

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