Tool wear mechanisms in machining of three titanium alloys with increasing <i>β</i>-phase fraction

Joshi, Shashikant; Pawar, Pravin; Tewari, Ashish; Joshi, Suhas S.

doi:10.1177/0954405414522796

Cited by 21 publications

(21 citation statements)

References 15 publications

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“…The change in grain structure from a to b structure also causes changes in mechanical properties, chip formation and tool wear mechanism. 10 Micromachining of such materials is thus a more complicated science than simple scaling down of tool-workpiece dimensions, as the micro-tool transits between a and b grains that leads to more complicated tool dynamics and wear mechanisms that are essentially different from conventional/macro-machining. Very little research on mechanical micromachining of titanium alloys has been reported as compared with other materials.…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis of process parameters in micromachining of Ti-6Al-4V alloy

Jaffery

Khan

Ali

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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The demand for miniaturized components is on the rise, especially from the biomedical and aerospace industry. As a result, there is a strong research potential towards the micro-manufacturing of biomedical and aerospace components. Titanium-based alloys are known for their biocompatibility and high strength-to-weight ratio, making them most suitable for such applications. In this research, flank wear progression, surface roughness and side burrs, the basic performance parameters of a typical micromachining operation, are presented and analysed through analysis of variance in order to determine the key process parameters. It was found that micromachining can be classified into two categories: micromachining with undeformed chip thickness below the tool edge radius and micromachining keeping the undeformed chip thickness above the tool edge radius. The results showed that when machining with undeformed chip thickness above edge radius, the feedrate remains the most significant parameter affecting tool wear (41% contribution ratio), surface roughness (83%) and burr width (80%). This result places this type of machining closer to macro-machining where feed contribution was found to be 69%, 92% and 75% as against micromachining below edge radius, where contributions stood at 17%, 53% and 52% on tool wear, surface roughness and burr width, respectively. The results underscored the importance of considering the tool edge radius in micromachining.

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Section: Introductionmentioning

confidence: 99%

Statistical analysis of process parameters in micromachining of Ti-6Al-4V alloy

Jaffery

Khan

Ali

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…The effect of varying fraction of β-phase in titanium alloys was experimentally investigated on the tool wear characteristics of a turning process. 34 Abrasion, abrasion with built-up edge, and plastic deformation of cutting edge were found to be the main tool damage mechanisms in α, α + β, and β-rich alloy, respectively.…”

Section: Introductionmentioning

confidence: 98%

Investigating the impact of tool inertia on machinability of a β-titanium alloy using tool deflection and acoustic emission

Iqbal

Biermann

Ali

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part B:

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Finding sustainable ways of machining exotic materials is gaining more and more importance in the manufacturing industry. Application of advanced measuring instruments for quantifying performance measures is a crucial requirement for making machining processes viable. The presented work aims to ameliorate machining of a high-strength β-titanium alloy using information from measurements of key responses, such as cutting energy consumption, tool deflection, and tool damage. Acoustic emission data and tool’s acceleration data are utilized to work out the magnitudes of energy consumed and deflection undergone by the tool, respectively. The article focuses on quantifying the effects of tool’s inertia, strength of work material, and two cutting parameters on the aforementioned responses. A total of 54 continuous cutting experiments are performed in which a fixed volume of material per experimental run is removed. Tool deflection method helped to determine the significant effects of varying tool inertia, work material strength, and cutting speed on the machining process. Likewise, acoustic emission method highlighted the strong effects of material strength and cutting speed caused on the cutting energy consumption. The effect of feed rate is found to be significant regarding tool wear only. Finally, the tool wear data are tested for correlation against the corresponding data sets of the other two responses. It is found that both tool deflection and cutting energy possess strong uphill relationships with tool wear.

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“…15 Abrasion with built-up edge and plastic deformation of the cutting edge are found to be dominant in the machining of titanium alloys with different β fractions. 16,17 Although studies on the tool-wear behaviour in machining are as old as metal cutting, 18,19 one of the earliest efforts to quantify tool life is attributed to the tool life equation by FW Taylor 20 and its modified versions, which relates the tool life with machining parameters. A number of analytical models are proposed by researchers for the tool-wear prediction in different cutting applications and tool–workpiece combinations.…”

Section: Introductionmentioning

confidence: 99%

Worn tool geometry–based flank wear prediction in micro turning

Elias

Asams

Mathew

2019

Proceedings of the Institution of Mechanical Engineers, Part B:

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Mechanical micromachining techniques have gained much popularity in the manufacturing of microcomponents with complex shapes in the past couple of decades. Machining at the microscale poses several challenges such as size effect, which highly influences the material deformation mechanism resulting in a nonlinear variation in specific cutting energy, which accelerates the tool wear. Since micromachining is associated with micro-features, high precision and tight tolerances, the prediction of tool wear in advance is essential. Calibrated tool-wear models are generally used for the prediction of tool wear in the macro machining regime, whereas the applicability of these tool-wear models in the microscale machining is not explored much in the past. In the present work, Usui tool-wear model and worn tool geometry–based Malakizadi model are calibrated for the tool flank wear prediction during micro turning of Ti-6Al-4V alloy, using a hybrid approach involving both finite element simulations and cutting experiments. The validation experiments show that both the models can satisfactorily predict the tool-wear rate during micro turning with a percentage error of less than 15%. Results indicate that the worn tool geometry–based tool-wear model outperforms the conventional Usui model as it incorporates the instantaneous tool geometry, which also makes it suitable for different tool geometries.

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Tool wear mechanisms in machining of three titanium alloys with increasing β-phase fraction

Cited by 21 publications

References 15 publications

Statistical analysis of process parameters in micromachining of Ti-6Al-4V alloy

Statistical analysis of process parameters in micromachining of Ti-6Al-4V alloy

Investigating the impact of tool inertia on machinability of a β-titanium alloy using tool deflection and acoustic emission

Worn tool geometry–based flank wear prediction in micro turning

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