Optimization of flatness of strip during coiling process based on evolutionary algorithms

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

doi:10.1007/s12541-015-0198-7

Cited by 13 publications

(5 citation statements)

References 25 publications

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“…This kind of directional mutation has the same concept of the well-known opposition based method presented for improving the DE performance in the literature [22,23]. This rule guarantees that the differential variation is oriented toward a better vector, thus increasing the possibility of creating an improved solution.…”

Section: Modification In Mutation: the Random Directional Mutationmentioning

confidence: 99%

Weight optimisation of functionally graded beams using modified differential evolution

Pham

Duong

2019

STCE

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In this article, an efficient numerical approach for weight optimisation of functionally graded (FG) beams in the presence of frequency constraints is presented. For the analysis purpose, a finite element (FE) solution based on the first order shear deformation theory (FSDT) is established to analyse the free vibration behaviour of FG beams. A four-parameter power law distribution and a five-parameter trigonometric distribution are used to describe the volume fraction of material constituents in the thickness direction. The goal is to tailor the thickness and material distribution for minimising the weight of FG beams while constraining the fundamental frequency to be greater than a prescribed value. The constrained optimisation problem is effectively solved by a novel differential evolution (DE) algorithm. The validity and efficiency of the proposed approach is demonstrated through two numerical examples corresponding to the four-parameter distribution and the five-parameter distribution.Keywords: FGM beam; lightweight design; frequency constraint; differential evolution.

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Section: Modification In Mutation: the Random Directional Mutationmentioning

confidence: 99%

Weight optimisation of functionally graded beams using modified differential evolution

Pham

Duong

2019

STCE

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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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“…[1][2][3][4] The coiling process, as the last step of the production line, also affects the final performance of the product. 5,6) The stress state inside the coil directly determines whether defects will occur, such as surface quality damage caused by sliding between adjacent layers, collapse after unloading, and plastic deformation of the inner layers and sleeve caused by excessive radial stress. [7][8][9][10] However, it is difficult to measure the internal stress state during the coiling process through experiments.…”

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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Optimization of flatness of strip during coiling process based on evolutionary algorithms

Cited by 13 publications

References 25 publications

Weight optimisation of functionally graded beams using modified differential evolution

Weight optimisation of functionally graded beams using modified differential evolution

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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