Influence of friction models on FE simulation results of orthogonal cutting process

Malakizadi, Amir; Hosseinkhani, Keyvan; Mariano, Emilia; Ng, E. G.; Prete, Antonio Del; Nyborg, Lars

doi:10.1007/s00170-016-9023-4

Cited by 44 publications

(20 citation statements)

References 47 publications

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“…This should be considered when evaluating the performance of JC parameters reported in the literature. A similar observation was made by Malakizadi et al [37] by comparing the simulation results obtained from DEFFORM, AdvantEdge, and ABAQUS for machining AISI1045 and AISI 1080 plain carbon steels. The results for AA6082 are shown in Fig.…”

Section: Performance Of Calibrated Materials Parameterssupporting

confidence: 77%

“…The limits for n and m are 0-0.25 and 0.9-1.1, respectively, for both C38 and 42CrMo4. These range of restrictions are selected based on available data in the literature [11,15,21,[27][28][29][30][31][32][33][34][35][36][37][38][39][40][41].…”

Section: Identified Materials Parametersmentioning

confidence: 99%

“…For that purpose, we tried to repeat the same simulations performed in the references by using the same parameters and boundary conditions with the only difference being the JC parameters. Also, the pressuredependent shear friction model is a good representative for the complex frictional behavior at the chip-insert contact [37]. Because of these reasons and to represent nonlinear frictional behavior in machining, the pressure-dependent shear friction model is implemented for simulations of C38 workpiece material.…”

Section: Simulation Detailsmentioning

confidence: 99%

See 2 more Smart Citations

A thermomechanically motivated approach for identification of flow stress properties in metal cutting

Erturk

Malakizadi

Larsson

2020

Int J Adv Manuf Technol

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The paper presents a novel thermomechanically coupled distributed primary deformation zone model to assist the inverse identification of Johnson-Cook material parameters to be used for machining simulations. A special feature of the enhanced model is that the assumed stress field is temperature-dependent, where the thermomechanical coupling governs the stress and temperature distributions across the primary shear zone to describe the thermal softening effect. By using stress, strain, strain rate, and temperature distributions from the thermomechanically enhanced model, Johnson-Cook material parameters are calibrated for orthogonal cutting tests of C38, 42CrMo4, and AA6082 materials where continuous chip formation prevails. The performance of the parameters is compared with that of a wider set of cutting tests using finite element simulations. The results show that the thermomechanically motivated model yields closer results to experiments in terms of cutting force and chip thickness (9% and 34% difference, respectively) compared with the original thermally uncoupled model (47% and 92% difference, respectively). Identification of the material parameters by this method focuses directly on the orthogonal cutting test and it does not require many experiments or simulations. In fact, the proposed methodology is computationally robust and cost-efficient which makes it preferable compared with other methods which are more accurate but highly time-consuming.

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Section: Performance Of Calibrated Materials Parameterssupporting

confidence: 77%

Section: Identified Materials Parametersmentioning

confidence: 99%

Section: Simulation Detailsmentioning

confidence: 99%

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A thermomechanically motivated approach for identification of flow stress properties in metal cutting

Erturk

Malakizadi

Larsson

2020

Int J Adv Manuf Technol

Self Cite

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show abstract

“…The constitutive models of commonly used metal cutting models are: the Zener-Holloman constitutive model, Bodner-Partom constitutive relation model, constitutive equation in the form of power function, interpolation constitutive equation and Johnson-Cook (J-C) constitutive equation. Among them, the J-C constitutive model is applicable to various crystal structures in its simple form and is, therefore, widely used [24]. The equation is:…”

Section: ) Finite Element Modelling Of the Cutting Processmentioning

confidence: 99%

Modeling and Analysis of the Reliability of Machining Process of Diesel Engine Blocks Based on PFMECA

Tian

Zhang

et al. 2019

IEEE Access

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Due to its difficulty in maintenance, the diesel engine have special requirements on process reliability of the engine block, which is one of the most important and hard-to-machining components of the engine, and will directly affects the performance and service life of the engine. With continuous improvements to the engine quality, the process reliability of the engine block have become more and more important. However, the previous researches mainly focus on the reliability of products, machine tools, or cutting tools, while the researches on the reliability of machining process, which lead to unstable quality of the machined engine block, have been little discussed. Therefore, this paper proposes an integrated method to analyze the process reliability of DEB (Diesel Engine Blocks). First, the reliability model of the DEB machining process is established by using reliability block diagram method. The model is mainly concerned with the process reliability and error-free judgment probability of the key features of DEB, which is deduced by using the PFMECA (Process Failure Mode, Effects and Criticality Analysis) method. Then, the response surface and FEM method is used to establish a mathematical model for the key features and its key influencing factors, and the process reliability of the key features is evaluated by Monte Carlo simulation. The reliability of the machining process is evaluated by substituting the process reliability of the key features into the reliability model of the DEB machining process. The method is applied to evaluate the reliability of the machining process of a certain type of DEB and solves the problem that the actual machining data are insufficient for reliability evaluation.

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“…The model incorporated for simulating the frictional condition at the tool-chip interface is vital for an accurate chip formation process. Malakizadi et al [45] studied the influence of the friction model on FE simulation results. All friction models resulted to an identical range of minimum average error.…”

Section: Contact and Friction Modelmentioning

confidence: 99%

A framework for simulation-based multi-objective optimization and knowledge discovery of machining process

Amouzgar

Bandaru

Andersson

et al. 2018

Int J Adv Manuf Technol

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The current study presents an effective framework for automated multi-objective optimization (MOO) of machining processes by using finite element (FE) simulations. The framework is demonstrated by optimizing a metal cutting process in turning AISI-1045, using an uncoated K10 tungsten carbide tool. The aim of the MOO is to minimize tool-chip interface temperature and tool wear depth, that are extracted from FE simulations, while maximizing the material removal rate. The effect of tool geometry parameters, i.e., clearance angle, rake angle, and cutting edge radius, and process parameters, i.e., cutting speed and feed rate on the objective functions are explored. Strength Pareto Evolutionary Algorithm (SPEA2) is adopted for the study. The framework integrates and connects several modules to completely automate the entire MOO process. The capability of performing the MOO in parallel is also enabled by adopting the framework. Basically, automation and parallel computing, accounts for the practicality of MOO by using FE simulations. The trade-off solutions obtained by MOO are presented. A knowledge discovery study is carried out on the trade-off solutions. The non-dominated solutions are analyzed using a recently proposed data mining technique to gain a deeper understanding of the turning process.

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Influence of friction models on FE simulation results of orthogonal cutting process

Cited by 44 publications

References 47 publications

A thermomechanically motivated approach for identification of flow stress properties in metal cutting

A thermomechanically motivated approach for identification of flow stress properties in metal cutting

Modeling and Analysis of the Reliability of Machining Process of Diesel Engine Blocks Based on PFMECA

A framework for simulation-based multi-objective optimization and knowledge discovery of machining process

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