Numerical and experimental study of contact behavior in the tool-based micromachining of steel

Woon, Keng Soon; Rahman, M.; Liu, Kui

doi:10.1007/s12541-010-0052-x

Cited by 8 publications

(5 citation statements)

References 15 publications

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“…The Coulomb friction model and the sticking-sliding friction model were considered. Woon and colleagues analyzed the contact length in the micro-cutting process numerically and experimentally [54]. They showed good agreement between the values obtained by simulation and experimental studies using the optical method.…”

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confidence: 83%

Determination of the Tool–Chip Contact Length for the Cutting Processes

et al. 2022

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The thermomechanical interaction of the tool with the chip in the most loaded secondary cutting zone depends on the contact length of the tool rake face with the chip. Experimental studies of the dependency of the contact length on the cutting speed, the undeformed chip thickness, and the tool rake angle, performed by the optical method, are used for comparison with the contact length obtained by the FE modeling of the orthogonal cutting process. To determine the parameters of the constitutive Johnson–Cook equation, which serves as a material model of the FE cutting model that has a predominant influence on the contact length, a software-implemented algorithm was developed. This algorithm is based on determining the generalized parameters of the constitutive equation through finding the intersection of these parameter sets. The plurality intersection of the parameter sets of the constitutive equation is determined by means of the design of experiments and refined by subsequent multiple iterations. The comparison of the contact length values, obtained by simulating the cutting process using the generalized parameters of the constitutive equation as a material model with their experimental values, does not exceed 12% for a wide range of cutting speeds and depths of cut, as well as for the tool rake angle.

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confidence: 83%

Determination of the Tool–Chip Contact Length for the Cutting Processes

et al. 2022

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“…First model was created by taking similar parameter as model published in [10]. A medium carbon steel (AISI1045) workpiece is machined at cutting speed of 100m/min by micro cutting tool under various undeformed chip thickness.…”

Section: Methodsmentioning

confidence: 99%

Temperature Distribution of Micro Milling Process due to Uncut Chip Thickness

Baharudin

Sulaiman

et al. 2014

AMR

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A simplified model for micro milling process is presented, as well as results on temperature on tool and work piece. The purpose is to investigate on finite element modelling of two flute micro end milling process of titanium alloy, Ti6Al4V with prediction of temperature distribution. ABAQUS/Explicit has been chosen as solver for the analysis. A thermo-mechanical analysis was performed. First model was created by selecting medium carbon steel, AISI1045, as workpiece material for model validation purpose. Second model was created by modifying the workpiece material from AISI1045 to Ti6Al4V. The model consists of two parts which are tungsten carbide micro tool and workpiece. Johnson-Cook law model has been applied as material constitutive properties for both materials due to its severe plastic deformation occur during machining. Prediction on forces was obtained during the analysis. Model validation was done by comparing results published by Woon et al. in 2008. The results showed a good agreement in cutting force. Once this was proved, the same model was then modified to simulate finite element analysis in micro milling of Ti6Al4V. Prediction of temperature distribution of micro end mill of Ti6Al4V was done in relation of different undeformed chip thickness. The findings showed that temperature increases as undeformed chip thickness increases. Temperature distribution of Ti6Al4V and AISI1045 under same machining conditions was compared. Results showed that the highest temperature was concentrated at tool edge for Ti6Al4V.

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“…Similarly to most of the literature on the topic [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28], the AISI 1045 steel workpiece was modelled with the JohnsonCook material model [29]. The popularity of this model is due to its capability of describing behaviour of metals in processes where large strains, high strain rates, temperature dependency and visco-plastic deformation are included.…”

Section: Materials Model 341 Workpiece -Aisi 1045mentioning

confidence: 99%

“…The values of these parameters for the investigated AISI 1045 steel are taken from the literature [22,25,26,30], and can be found in Table 5.…”

Section: Materials Model 341 Workpiece -Aisi 1045mentioning

confidence: 99%