Efficient hybrid evolutionary algorithm for optimization of a strip coiling process

Pholdee, Nantiwat; Park, Won-Woong; Kim, Dong Kyu; Im, Yong‐Taek; Bureerat, Sujin; Kwon, Hyuck-Cheol; Chun, Myung-Sik

doi:10.1080/0305215x.2014.905551

Cited by 14 publications

(5 citation statements)

References 30 publications

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“…The optimization problem of improving the strip flatness in a strip coiling process was solved by the efficient metaheuristic in [22]. It is based on the differential evolution and the hybridization of teaching-learning-based optimization.…”

Section: Overview Of Thermal Properties Researchmentioning

confidence: 99%

Thermophysical Properties Estimation in Annealing Process Using the Iterative Dynamic Programming Method and Gradient Method

Durdán¹,

Kačur²,

Laciak³

et al. 2019

Energies

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In annealing, steel coils should be heated and consequently cooled according to the technological prescription defined for the annealed type of steel. It is appropriate to develop the systems and methods for estimation of the steel coil inner temperature for that reason. The proposal for such a system of indirect measurement of inner temperature is described in this study. This system, in the form of the mathematical model, is developed based on the theory of heat transfer and needs thermophysical parameters as inputs. In many cases, the thermophysical properties are difficult to access or unknown for the specific composition of the material being processed. In this paper, two optimization methods were applied to estimate two thermophysical properties. The application of the iterative dynamic programming method is aimed to estimate optimal thermal diffusivity. The verification of this method was performed on 11 laboratory measurements. The algorithm of the gradient method was used for estimating thermal conductivity and was verified on seven operational measurements. Results show that the optimized values of thermophysical properties increased the accuracy of the steel coil inner temperature estimation in the locations nearer to the steal coil central axis.

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Section: Overview Of Thermal Properties Researchmentioning

confidence: 99%

Thermophysical Properties Estimation in Annealing Process Using the Iterative Dynamic Programming Method and Gradient Method

Durdán¹,

Kačur²,

Laciak³

et al. 2019

Energies

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“…Optimisation of a strip coiling process using mate-heuristic Up to recently, we have studied using a number of meta-heuristics in solving the optimum strip coiling process posed to alleviate the strip wavy edges during coiling. The optimisers include differential evolution (DE) [3], simulated annealing (SA) [4], artificial bee colony optimisation (ABC) [5], teaching-learning based optimisation (TLBO) [6], real code ant colony optimisation (ACOR) [7], league championship algorithm (LCA) [8], Opposition-based Differential Evolution Algorithm (OPDE) [9], charged system search (ChSS) [10], Enhanced teaching-learning based optimisation with differential evolution (ETLBO-DE) [2] and improved teaching-learning based algorithm (ITLBO) [11]. They were used to solve the problem for five optimisation runs with a population size of 100 and the number of iterations being 100 (100100 function evaluations).…”

Section: Problem Formulationmentioning

confidence: 99%

Meta-Heuristics for Engineering Optimisation - Applications to Metal Forming Processes

Pholdee

Bureerat

2017

KEM

Self Cite

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This paper presents the use of meta-heuristics one of the most popular types of optimisation methods for solving real engineering applications. The general procedure of meta-heuristics is detailed. The applications are related to metal forming processes. Two design examples, optimisation of a strip coiling process and the non-circular wire drawing process, are demonstrated. The results obtained are compared while advantages and disadvantages of using the optimisers are discussed.

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“…Therefore, simulating the coiling process to predict the internal stress state of the coil is of great significance in reducing the occurrence of defects and improving the product quality. [11][12][13][14] The analytical method is the simplest and most efficient. Sims et al 15) simplified the coiling process into thin-walled cylinders nested layer by layer on a thick-walled cylinder and adopted the axisymmetric assumption.…”

Section: Introductionmentioning

confidence: 99%

Efficient Finite Element Simulation of Cold Rolled Strip Coiling Process Considering Additional Contact Deformation between Layers

Dai,

Liang,

Qiu

et al. 2024

ISIJ Int.

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When analyzing the strip coiling process, the finite element (FE) method is closer to the actual working conditions compared to the analytical method. However, due to the large number of strip elements and contact elements, it often leads to problems such as long-time consumption and nonconvergence. Meanwhile, traditional FE methods are still unable to solve the problem of additional contact deformation between layers. Therefore, in order to overcome the shortcomings of the above methods, the FE software MSC Marc is used to establish a strip coiling model. The distribution pattern of interlayer friction and contact stress are analyzed to propose a new step-by-step bonding FE model, which greatly reduces the computing time. Through laminated compression experiments, the variation curve between additional contact deformation and pressure is obtained.The curve is introduced into the gasket elements to consider the additional contact deformation between the layers, and the effect of additional contact deformation between the layers on the stress of the coil and the pressure on the mandrel is studied. Finally, the analytical solution is compared with the FE solution proposed in this paper, and the errors generated by the analytical method are analyzed.

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Efficient hybrid evolutionary algorithm for optimization of a strip coiling process

Cited by 14 publications

References 30 publications

Thermophysical Properties Estimation in Annealing Process Using the Iterative Dynamic Programming Method and Gradient Method

Thermophysical Properties Estimation in Annealing Process Using the Iterative Dynamic Programming Method and Gradient Method

Meta-Heuristics for Engineering Optimisation - Applications to Metal Forming Processes

Efficient Finite Element Simulation of Cold Rolled Strip Coiling Process Considering Additional Contact Deformation between Layers

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