Experimental study on chip deformation of Ti-6Al-4V titanium alloy in cryogenic cutting

Zhao, Wei; Gong, Lian; Ren, Fei; Li, Liang; Xu, Qian; Khan, Aqib Mashood

doi:10.1007/s00170-018-1890-4

Cited by 38 publications

(13 citation statements)

References 27 publications

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“…Larger forces in dry grinding are due to the absence of cutting fluids, which leads to dulling of abrasive grits, premature breakage of grains and side flow of materials [41]. The results are in good agreement with the published literature, such as with the study of Sadeghi et al [40]. They have also claimed to have better surface quality and lower force while grinding.…”

Section: Resultssupporting

confidence: 67%

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Multi-Objective Optimization for Grinding of AISI D2 Steel with Al2O3 Wheel under MQL

et al. 2018

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In the present study, the machinability indices of surface grinding of AISI D2 steel under dry, flood cooling, and minimum quantity lubrication (MQL) conditions are compared. The comparison was confined within three responses, namely, the surface quality, surface temperature, and normal force. For deeper insight, the surface topography of MQL-assisted ground surface was analyzed too. Furthermore, the statistical analysis of variance (ANOVA) was employed to extract the major influencing factors on the above-mentioned responses. Apart from this, the multi-objective optimization by Grey–Taguchi method was performed to suggest the best parameter settings for system-wide optimal performance. The central composite experimental design plan was adopted to orient the inputs wherein the inclusion of MQL flow rate as an input adds addition novelty to this study. The mathematical models were formulated using Response Surface Methodology (RSM). It was found that the developed models are statistically significant, with optimum conditions of depth of cut of 15 µm, table speed of 3 m/min, cutting speed 25 m/min, and MQL flow rate 250 mL/h. It was also found that MQL outperformed the dry as well as wet condition in surface grinding due to its effective penetration ability and improved heat dissipation property.

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Section: Resultssupporting

confidence: 67%

“…Overview of research on grinding types, the different materials used, and methods used [22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52]. …”

Section: Figurementioning

confidence: 99%

Multi-Objective Optimization for Grinding of AISI D2 Steel with Al2O3 Wheel under MQL

et al. 2018

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“…This is explained by the lubrication of liquid nitrogen applied on the tool insert-chip interface, insert surface of the flank of the workpiece machined, and in the cutting tool insert which resulted in a reduced cutting temperature, less adhesion between the workpiece surface generated and the tool auxiliary surface of the flank, and less tool wear on the insert edge. The LN 2 cooling with a coated cutting tool causes a decrease in the roughness of a workpiece surface (Ra) by 1-27% over an uncoated insert [27,28].…”

Section: Resultsmentioning

confidence: 99%

Investigation of AlCrN-Coated Inserts on Cryogenic Turning of Ti-6Al-4V Alloy

Selvam

Murugesan

Dhananchezian³

et al. 2019

Metals

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Over the past decade, the focus of the metal cutting industry has been on the improvement of tool life for achieving higher productivity and better finish. Researchers are attempting to reduce tool failure in several ways such as modified coating characteristics of a cutting tool, conventional coolant, cryogenic coolant, and cryogenic treated insert. In this study, a single layer coating was made on cutting carbide inserts with newly determined thickness. Coating thickness, presence of coating materials, and coated insert hardness were observed. This investigation also dealt with the effect of machining parameters on the cutting force, surface finish, and tool wear when turning Ti-6Al-4V alloy without coating and Physical Vapor Deposition (PVD)-AlCrN coated carbide cutting inserts under cryogenic conditions. The experimental results showed that AlCrN-based coated tools with cryogenic conditions developed reduced tool wear and surface roughness on the machined surface, and cutting force reductions were observed when a comparison was made with the uncoated carbide insert. The best optimal parameters of a cutting speed (V c ) of 215 m/min, feed rate (f) of 0.102 mm/rev, and depth of cut (doc) of 0.5 mm are recommended for turning titanium alloy using the multi-response TOPSIS technique. on the workpiece materials and cutting conditions [2]. Various coated cutting tools (e.g., TiN, TiAlN, AlTiN, CrN) are available on the market, but machining of Ti alloy still sees problems like the formation of built-up edges on the tools, a rise in wear marks on the cutting edges, and poor quality of machined surfaces. Hence, it is vital to assess the machinability characteristics of Ti alloys in the turning operation using appropriate coatings on cutting tools and advanced techniques of cryogenic lubrication.Chauhan and Rawal [3] reported on nitride ion-based coatings, such as TiAlN, TiMoN, and TiVN, with different deposition techniques. They implied ternary nitride-based coatings showing a higher improvement in tribological and mechanical properties compared to the binary nitride coatings. Bouzakis et al. [4] discussed the evolution of cutting tool coating elements, related coating deposition techniques, manufacturing methods, recent characterization methods, film dimensional thickness, and recondition of wear on coated cutting tools. Their paper shows that as productivity increases, so does the need for improvement. Biksa et al. [5] analyzed the self-adaptive functional coating on cutting tools while machining nickel and titanium-based alloys. It showed the attainment of a better life for AlTiN/MoN-coated tools when machining Inconel 781 and AlTiN/VN-coated tools for Ti-Al6-V4 alloy. This coating was seen as having a smaller coefficient of friction at specific elevated temperatures. Nordegren et al. [6] investigated the plastic deformation modeling on layered carbide tool edges when machining AISI 4340 steel. The result indicated a determined finite element model for the edge thermal effect of the machining process.Ghani et al....

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“…Overall, better surface roughness values are achieved, this is due to excellent cooling and lubrication provided by the vegetable oil. 34 Figure 7 represents the effects of depth of cut and feed on surface roughness. Increasing trend in surface roughness value is observed with the increase in feed rate.…”

Section: Rsm-based Model Analysismentioning

confidence: 99%

Multi-objective optimisation for minimum quantity lubrication assisted milling process based on hybrid response surface methodology and multi-objective genetic algorithm

Mumtaz

Imran

et al. 2019

Advances in Mechanical Engineering

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Parametric modelling and optimisation play an important role in choosing the best or optimal cutting conditions and parameters during machining to achieve the desirable results. However, analysis of optimisation of minimum quantity lubricationassisted milling process has not been addressed in detail. Minimum quantity lubrication method is very effective for cost reduction and promotes green machining. Hence, this article focuses on minimum quantity lubrication-assisted milling machining parameters on AISI 1045 material surface roughness and power consumption. A novel low-cost power measurement system is developed to measure the power consumption. A predictive mathematical model is developed for surface roughness and power consumption. The effects of minimum quantity lubrication and machining parameters are examined to determine the optimum conditions with minimum surface roughness and minimum power consumption. Empirical models are developed to predict surface roughness and power of machine tool effectively and accurately using response surface methodology and multi-objective optimisation genetic algorithm. Comparison of results obtained from response surface methodology and multi-objective optimisation genetic algorithm depict that both measured and predicted values have a close agreement. This model could be helpful to select the best combination of end-milling machining parameters to save power consumption and time, consequently, increasing both productivity and profitability.

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Experimental study on chip deformation of Ti-6Al-4V titanium alloy in cryogenic cutting

Cited by 38 publications

References 27 publications

Multi-Objective Optimization for Grinding of AISI D2 Steel with Al2O3 Wheel under MQL

Multi-Objective Optimization for Grinding of AISI D2 Steel with Al2O3 Wheel under MQL

Investigation of AlCrN-Coated Inserts on Cryogenic Turning of Ti-6Al-4V Alloy

Multi-objective optimisation for minimum quantity lubrication assisted milling process based on hybrid response surface methodology and multi-objective genetic algorithm

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