Design of a Modular Green Closed Internal Cooling Turning Tool for Applications

Wu, Tao; Li, Tianjian; Ding, Xuanming; Hong, Chen; Wang, Lei

doi:10.1007/s40684-018-0021-x

Cited by 21 publications

(18 citation statements)

References 15 publications

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“…Consequently, tool temperature was reduced in SCC condition. This was in agreement the investigation conducted by Minton et al [15] and Wu et al [29]. They reported that internally cooled tool signi cantly exhibited a reduction in its temperature.…”

Section: Heat Distribution On Rake Facesupporting

confidence: 92%

Effects of submerged convective cooling in the turning of AZ31 magnesium alloy for tool temperature and wear improvement

Zakaria

Mustapha

Azmi

et al. 2022

Int J Adv Manuf Technol

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Low melting point and material adhesion attributed by the magnesium alloy led to extreme built-up edge (BUE) and built-up layer (BUL) formations. Dry machining is favourable for machining magnesium alloy; however, this strategy in icts excessive adhesive wear on the cutting tool. Therefore, this current work focuses on innovative cooling technique known as submerged convective cooling (SCC) for the turning of the AZ31 magnesium alloy. Prior to cutting experiment, a computational uid dynamics (CFD) simulation was conducted to evaluate internal structure of cooling module. Based on the CFD simulation, small inlet/outlet diameter signi cantly contribute to reduction of tool temperature because of effective heat transfer coe cient of cooling uid in the SCC. Experimental results revealed that SCC has effectively reduced the tool temperature by 50% and contributed to 37% improvement in surface roughness when compared to dry cutting. Finally, both BUE and BUL were observed in dry and SCC conditions, but the severity of these wear mechanisms improved or decreased remarkably under SCC conditions.

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Section: Heat Distribution On Rake Facesupporting

confidence: 92%

Effects of submerged convective cooling in the turning of AZ31 magnesium alloy for tool temperature and wear improvement

Zakaria

Mustapha

Azmi

et al. 2022

Int J Adv Manuf Technol

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“…The most common way to address the control of the high temperatures experienced during mechanical cutting has been with the use of external water-based coolants [ 2 – 4 ]. However, there is general recognition that the wide use of these substances has a detrimental effect on the environment once removed as waste disposal [ 5 , 6 ]. Additionally, the chemical composition itself can have a direct impact on the health of the operator over time [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Study on magnetohydrodynamic internal cooling mechanism within an aluminium oxide cutting tool

O’Hara,

Fang

2024

Int J Adv Manuf Technol

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One of the challenges in the transfer of heat during the mechanical machining process is the coolant substance used in the internal cooling method which is generally liquid water or a water-based coolant. This limits the heat transfer capacity insofar as the thermal conductivity of liquid water is concerned. The other difficulty is the requirement for an external mechanical system to pump the coolant around the internal channel, providing efficient transfer of the accumulated thermal energy. This study proposes a novel method to address this issue by using liquid gallium which provides the means to transfer the excess heat generated during the cutting process by integrating the design into an aluminium oxide insert. Combining this with a magnetohydrodynamic drive, the coolant system operates without the need for mechanical input. Liquid gallium is nontoxic and has a much higher thermal conductivity over liquid water. Investigations of the novel cooling system is performance compared against liquid water through numerical modelling, followed by an experimental machining test to ascertain the difference in heat transfer effectiveness, tool wear rates and workpiece surface finish when compared to dry machining and external cooling conditions on stainless steel 316L. Without cooling, experimental machining tests employing a cutting speed of Vc = 250 m min−1 resulted in a corner wear VBc rate of 75 μm, and with the magnetohydrodynamic-based coolant on, produced a VBc rate of 48 μm, indicating a difference of 36% in relative tool wear under the same cutting conditions. Increasing the cutting speed Vc to 900 m min−1, produced a corner wear VBc rate of 357 μm without the active coolant and a VBc rate of 246 μm with the magnetohydrodynamic-based coolant on, representing a decrease of 31% in relative tool wear. Further tests comparing external liquid water cooling against the liquid gallium coolant showed at Vc = 250 m min−1, a difference of 29% in relative tool wear rate reduction was obtained with the internal liquid gallium coolant. Increasing the cutting speed to Vc = 900 m min−1, the data indicated a difference of 16% relative tool wear reduction with the internal liquid gallium. The results support the feasibility of using liquid gallium as an internal coolant in cutting inserts to effectively remove thermal energy.

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“…Green machining, such as dry cutting without cooling liquid, has been aggressively pursued in the manufacturing industry in recent years [1]. Tools are the most vulnerable components in milling processes conducted using numerical control (NC) milling machines due to their direct contact with the surfaces of workpieces [2,3].…”

Section: Introductionmentioning

confidence: 99%

A GAPSO-Enhanced Extreme Learning Machine Method for Tool Wear Estimation in Milling Processes Based on Vibration Signals

Lei

Zhu

Zhou

et al. 2021

Int. J. of Precis. Eng. and Manuf.-Green Tech.

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Tools are the most vulnerable components in milling processes conducted using numerical control milling machines, and their wear condition directly influences work-product quality and operational safety. As such, tool wear estimation is an essential component of NC milling operations. This study addresses this issue by proposing an extreme learning machine (ELM) method enhanced by a hybrid genetic algorithm and particle swarm optimization (GAPSO) approach for conducting tool wear estimation based on workpiece vibration signals. Here, a few feature parameters in the time, frequency, and time-frequency (Ensemble empirical mode decomposition, EEMD) domains of the workpiece vibration signals are extracted as the input of the ELM model. Then, the initialized weights and thresholds of the ELM model are optimized based on the GAPSO approach with training dataset. Finally, tool wear is estimated using the optimized ELM model with testing dataset. The effectiveness of the proposed method is verified by its application to vibration signals collected from two milling tool wear experiments (an open-access benchmark dataset and a milling tool wear experiment) by comparison to the ELM, GA-ELM, and PSO-ELM methods. The results indicate that the estimation accuracy and optimization efficiency of the proposed method outperforms that of other three methods.

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Design of a Modular Green Closed Internal Cooling Turning Tool for Applications

Cited by 21 publications

References 15 publications

Effects of submerged convective cooling in the turning of AZ31 magnesium alloy for tool temperature and wear improvement

Effects of submerged convective cooling in the turning of AZ31 magnesium alloy for tool temperature and wear improvement

Study on magnetohydrodynamic internal cooling mechanism within an aluminium oxide cutting tool

A GAPSO-Enhanced Extreme Learning Machine Method for Tool Wear Estimation in Milling Processes Based on Vibration Signals

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