Electroplastic cutting influence on power consumption during drilling process

Hameed, Shafqat; Rojas, Hernan Alberto González; Egea, Antonio J. Sánchez; Alberro, Amelia Nápoles

doi:10.1007/s00170-016-8562-z

Cited by 36 publications

(14 citation statements)

References 23 publications

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“…However, the results are in agreement with the previous study [25], in which current density decreases with the increase in cutting feed during electrically assisted drilling process. As the chip formation zone decreases with increase cutting speed, this may be the reason why current density values are higher at high cutting speeds for steel S235 during electrically assisted turning process.…”

Section: Resultssupporting

confidence: 93%

“…Hence, due to thermal contribution of EPs, the deformation resistance decreases [31], which ultimately decreases the SCE and improves the plasticity of material during EP assisted turning process. The results are also in agreement with Sánchez et al [24] and Hameed [25] where the SCE decreases due to the application of EPs during machining processes.…”

Section: Resultssupporting

confidence: 91%

“…The SCE is the quotient between the cutting power consumption and the material removal rate as described in the previous work [25]. The material removal rate,

Q_{c}

, is defined by the following equation:

Q_{c} = V_{c} \cdot f \cdot a_{b} (() 1 - \frac{a_{b}}{D})

where

V_{c}

is cutting speed (m/min) and D is the workpiece diameter (mm).…”

Section: Resultsmentioning

confidence: 99%

“…Sanchez et al [24] observed that the SCE and the power consumption are decreased when the turning process is assisted with EPs. In a previous study [25], it was found that, at lower feeds, when the higher current density is induced, the shear angle

ϕ

decreases and the chip compression ratio

ξ

increases during drilling process. There was no study or few attempts were made to evaluate the machinability of materials with respect to chip compression ratio

ξ

, shear plane angle

ϕ

and SCE while cutting with EPs during turning process.…”

Section: Introductionmentioning

confidence: 99%

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Influence of the Regime of Electropulsing-Assisted Machining on the Plastic Deformation of the Layer Being Cut

et al. 2018

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In this article, the influence of electropulsing on the machinability of steel S235 and aluminium 6060 has been studied during conventional and electropulsing-assisted turning processes. The machinability indices such as chip compression ratio ξ, shear plane angle ϕ and specific cutting energy (SCE) are investigated by using different cutting parameters such as cutting speed, cutting feed and depth of cut during electrically-assisted turning process. The results and analysis of this work indicated that the electrically-assisted turning process improves the machinability of steel S235, whereas the machinability of aluminium 6060 gets worse. Finally, due to electropluses (EPs), the chip compression ratio ξ increases with the increase in cutting speed during turning of aluminium 6060 and the SCE decreases during turning of steel S235.

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Section: Resultssupporting

confidence: 93%

Section: Resultssupporting

confidence: 91%

“…The SCE is the quotient between the cutting power consumption and the material removal rate as described in the previous work [25]. The material removal rate,

Q_{c}

, is defined by the following equation:

Q_{c} = V_{c} \cdot f \cdot a_{b} (() 1 - \frac{a_{b}}{D})

where

V_{c}

is cutting speed (m/min) and D is the workpiece diameter (mm).…”

Section: Resultsmentioning

confidence: 99%

ϕ

decreases and the chip compression ratio

ξ

increases during drilling process. There was no study or few attempts were made to evaluate the machinability of materials with respect to chip compression ratio

ξ

, shear plane angle

ϕ

and SCE while cutting with EPs during turning process.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Influence of the Regime of Electropulsing-Assisted Machining on the Plastic Deformation of the Layer Being Cut

et al. 2018

Self Cite

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show abstract

“…Machining is an important manufacturing methodology because of its precision, fast processing speed, and applicability to a broad class of materials. Conventional machining processes and non-conventional machining processes such as laser-assisted machining [1] and electrically assisted machining [2][3][4] have been widely used to transform bulk materials into products with desired geometry and functionality. Elevated temperature in conventional machining has a negative influence on tool performance, tool life, and the quality of machined parts because it softens tool materials and increases diffusion.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of an Analytical Model in the Prediction of Machining Temperature of AISI 1045 Steel and AISI 4340 Steel

Ning

Liang

2018

JMMP

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This paper evaluates a physics-based analytical model in the prediction of machining temperature of AISI 1045 steel and AISI 4340 steel. The prediction model was developed based on the Johnson-Cook constitutive model (J-C model) and mechanics of the orthogonal cutting process. The average temperatures at two shear zones were predicted by minimizing the difference between calculated stresses using the J-C model and calculated stresses using the mechanics model. In this work, (1) the influence of input Johnson-Cook model constants, cutting force, and chip thickness on the accuracy of predictions are investigated with sensitivity analyses, in which multiple sets of available J-C constants and varying cutting force and chip thickness are used for the temperature prediction in machining AISI 1045 steel. The larger the input deviation, the larger prediction deviation. The temperature at the primary shear zone is more susceptible to the deviation of inputs than the temperature at the secondary shear zone. (2) The machining temperatures are also predicted in machining AISI 4340 steel using cutting tools with various specifications to demonstrate its predictive capability. Good agreements are observed upon validation to available experimental data in the literature. (3) Lastly, the advantage and limitation of the temperature model are discussed with comparison other analytical temperature models. Considering the reliable and easily measurable input requirements and sufficient predictive capability, this temperature model can be employed for effective and efficient machining temperature prediction.

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Optimization of oak sawing parameters based on energy consumption and surface roughness

Hao,

Zhang,

et al. 2024

Materialwissenschaft Werkst

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High energy consumption and poor processing quality are common problems in wood sawing. To address these issues, in this article, specific cutting energy and surface roughness were investigated with saw blade speed as control variables. Analysing the effect of parameters on specific cutting energy and surface roughness. The sawing parameters were optimised with the objectives of minimum specific cutting energy and minimum surface roughness. The findings indicate that specific cutting energy and surface roughness reduction with increasing rake angle; specific cutting energy and surface roughness decrease with increasing spindle speed; specific cutting energy decreases and surface roughness increases with increasing feed rate. ANOVA analysis reveals that sawing speed (n) has the most significant impact on specific cutting energy during oak cutting. The optimal solution derived from TOPSIS suggests a specific cutting energy of 2E7 J/m3 and a surface roughness of 1.758 μm. The innovation of this paper is the study of the specific cutting energy and the optimisation of parameters. These findings provide valuable theoretical and practical guidance for enhancing the efficiency and quality of oak processing while minimizing energy consumption.

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Electroplastic cutting influence on power consumption during drilling process

Cited by 36 publications

References 23 publications

Influence of the Regime of Electropulsing-Assisted Machining on the Plastic Deformation of the Layer Being Cut

Influence of the Regime of Electropulsing-Assisted Machining on the Plastic Deformation of the Layer Being Cut

Evaluation of an Analytical Model in the Prediction of Machining Temperature of AISI 1045 Steel and AISI 4340 Steel

Optimization of oak sawing parameters based on energy consumption and surface roughness

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