Finite element analysis and response surface method for robust multi-performance optimization of radial turning of hard 300M steel

Sadeghifar, Morteza; Jomaa, Walid; Songmené, Victor

doi:10.1007/s00170-017-1032-4

Cited by 36 publications

(43 citation statements)

References 24 publications

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“…In the present section, these formulations together with the characteristics of the developed FE model are described. The equations of motion during cutting may be expressed at a specific instant of time as [14]:…”

Section: Finite Element Modelingmentioning

confidence: 99%

“…The convection heat transfer takes place between the workpiece surface and the ambient according to the following formulae [14]:…”

Section: Finite Element Modelingmentioning

confidence: 99%

“…This can be attributed to the resultant of two facts. The first fact is that a higher cutting speed generates larger frictional and plastic works, yielding more thermal softening, and as a result, produces smaller cutting forces during machining [14,21]. In contrast, the second fact is that a high cutting speed causes a greater material removal rate, leading to a lower cutting temperature and larger cutting forces [14,22].…”

Section: Validation Of the Fe Modelmentioning

confidence: 99%

See 2 more Smart Citations

On the impacts of tool geometry and cutting conditions in straight turning of aluminum alloys 6061-T6: an experimentally validated numerical study

Javidikia

Sadeghifar

Songmené

et al. 2020

Int J Adv Manuf Technol

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Aluminum alloys 6061-T6 are widely utilized in the automotive, aerospace and marine industries due to high corrosion resistance, high strength, and good workability and machinability. The machining performance of these alloys depend on several factors including tool's material, coating and geometry.Cutting tool edge radius is one of the most effective factors in cutting forces, energy requirement and chip formation during metal cutting. The present article aims to study the interactions between the cutting edge radius and cutting speed, feed rate and rake angle and examine the impacts of the aforementioned tool geometry and cutting conditions on machining forces, cutting temperature, and chip thickness in cutting an aluminum alloy 6061-T6. Special attention is devoted to examining the influence of the cutting edge radius on machining variables and comparing the results of conventional machining (CM) and high speed machining (HSM). A finite element model was developed to simulate the above intercations and was experimentally validated for different machining parameters. The results demonstrate that although increasing the cutting edge radius clearly raises the machining forces, it has a slight influence on the chip thickness. It is also found that the maximum cutting temperatures remain nearly constant with changes in the tool edge radius, while the average temperatures of the tool tip increase especially in HSM. Furthermore, it was found that the location at which the maximum cutting temperature occurs depends more on cutting conditions and tool geometry than workpiece and tool materials.

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Section: Finite Element Modelingmentioning

confidence: 99%

“…The convection heat transfer takes place between the workpiece surface and the ambient according to the following formulae [14]:…”

Section: Finite Element Modelingmentioning

confidence: 99%

Section: Validation Of the Fe Modelmentioning

confidence: 99%

See 1 more Smart Citation

On the impacts of tool geometry and cutting conditions in straight turning of aluminum alloys 6061-T6: an experimentally validated numerical study

Javidikia

Sadeghifar

Songmené

et al. 2020

Int J Adv Manuf Technol

Self Cite

View full text Add to dashboard Cite

show abstract

“…They may be divided in two main categories: (1) methods based on direct optimization of robustness, such as the Design of Experiments and the Taguchi robustness optimization method. Taguchi [19] introduced the quality loss theory into the product design and manufacturing process for establishing the tolerance design model, and took the output characteristic and its fluctuation as the basis for calculating the cost loss [20][21][22]. Later, scholars combined the cost and performance to establish the comprehensive quality loss function [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Quality and robustness optimization design method for electromagnetic devices consider manufacturing uncertainties and working point migration of permanent magnets

Chen

et al. 2020

SN Appl. Sci.

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Electromagnetic devices (EMDs) containing permanent magnets are common devices showing low power consumption , small size, and high sensitivity. In batch production of EMDs there is a robustness problem linked to the migration of the working point of permanent magnets and to their manufacturing uncertainties. In turn, the design optimization for EMDs has attracted large attention. Robust design optimization (RDO) is one of the most effective methods to boost quality and robustness of EMDs. However, state-of-art RDO methods ignore the various uncertainties from manufacture processing, production environment, and working point migration of permanent magnets. To address those problems, this study presents an efficient and universal method based on the working point migration and various uncertainties of output characteristics for electromagnetic devices. At first, we introduce a two-dimensional factor design scheme considering the working point migration and manufacturing conditions. Then, a robustness assessment measure suitable for different optimization types is proposed. On these bases, the optimization model is established, considering the permanent working point migration for magnets, manufacturing tolerances and robustness constraints, and a particle swarm algorithm is used to obtain the solution. Finally, the effectiveness of the method is verified by a case study involving a specific type of electromagnetic device with permanent magnets.

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“…The objectives were obtained by modelling the oblique turning process in ABAQUS FEM software. Recently, Sadeghifar et al (2018) performed an MOO on radial turning operation by using the a priori approach (a weighted sum method). A hybrid optimization, coupling genetic algorithm and sequential quadratic programming, optimized a combined function of tool temperature, cutting force and residual stresses.…”

Section: Introductionmentioning

confidence: 99%

Metamodel-based multi-objective optimization of a turning process by using finite element simulation

Amouzgar

Bandaru

Andersson

et al. 2019

Engineering Optimization

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This study investigates the advantages and potentials of the metamodelbased multi-objective optimization (MOO) of a turning operation through the application of finite element simulations and evolutionary algorithms to a metal cutting process. The objectives are minimizing the interface temperature and tool wear depth obtained from FE simulations using DEFORM-2D software, and maximizing the material removal rate. Tool geometry and process parameters are considered as the input variables. Seven metamodelling methods are employed and evaluated, based on accuracy and suitability. Radial basis functions with a priori bias and Kriging are chosen to model tool-chip interface temperature and tool wear depth, respectively. The non-dominated solutions are found using the strength Pareto evolutionary algorithm SPEA2 and compared with the non-dominated front obtained from pure simulation-based MOO. The metamodel-based MOO method is not only advantageous in terms of reducing the computational time by 70%, but is also able to discover 31 new non-dominated solutions over simulation-based MOO. ARTICLE HISTORY

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Finite element analysis and response surface method for robust multi-performance optimization of radial turning of hard 300M steel

Cited by 36 publications

References 24 publications

On the impacts of tool geometry and cutting conditions in straight turning of aluminum alloys 6061-T6: an experimentally validated numerical study

On the impacts of tool geometry and cutting conditions in straight turning of aluminum alloys 6061-T6: an experimentally validated numerical study

Quality and robustness optimization design method for electromagnetic devices consider manufacturing uncertainties and working point migration of permanent magnets

Metamodel-based multi-objective optimization of a turning process by using finite element simulation

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