Influences of milling and grinding on machined surface roughness and fatigue behavior of GH4169 superalloy workpieces

Li, Xun; Guan, Chunming; Zhao, Peng

doi:10.1016/j.cja.2017.07.013

Cited by 58 publications

(15 citation statements)

References 14 publications

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“…It is generally known that the higher surface roughness can cause dehancement in the tribological performance and provide crack initiation, which eventually leads to fatigue. For example, mechanical surface milling that had the lowest surface roughness values, also showed the highest improvement in the tribological performance [ 8 ]. Considering the roughness effect for improving tribological performance, it is advantageous to include UNSM treatment.…”

Section: Resultsmentioning

confidence: 99%

Better Surface Integrity and Tribological Properties of Steel Sintered by Powder Metallurgy

et al. 2020

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The current research reports the improvement in surface integrity and tribological characteristics of steel prepared using a powder metallurgy (PM) by ultrasonic nanocrystal surface modification (UNSM) at 25 and 300 °C. The surface integrity and tribological properties of three samples, namely, as-PM, UNSM-25 and UNSM-300 were investigated. The average surface roughness (Ra) of the as-PM, UNSM-25 and UNSM-300 samples was measured using a non-contact 3D scanner, where it was found to be 3.21, 1.14 and 0.74 µm, respectively. The top surface hardness was also measured in order to investigate the influence of UNSM treatment temperature on the hardness. The results revealed that the as-PM sample with a hardness of 109 HV was increased up to 165 and 237 HV, corresponding to a 32.1% and 57.2% after both the UNSM treatment at 25 and 300 °C, respectively. XRD analysis was also performed to confirm if any changes in chemistry and crystal size were took place after the UNSM treatment at 25 and 300 °C. In addition, dry tribological properties of the samples were investigated. The friction coefficient of the as-PM sample was 0.284, which was reduced up to 0.225 and 0.068 after UNSM treatment at 25 and 300 °C, respectively. The wear resistance was also enhanced by 33.2 and 52.9% after UNSM treatment at both 25 and 300 °C. Improvements in surface roughness, hardness and tribological properties was attributed to the elimination of big and deep porosities after UNSM treatment. Wear track of the samples and wear scar of the counter surface balls were investigated by SEM to reach a comprehensive discussion on wear mechanisms. Overall, it was confirmed that UNSM treatment at 25 and 300 °C had a beneficial effect on the surface integrity and tribological characteristics of sintered steel by the PM that is used in a shock absorber for a car engine.

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Section: Resultsmentioning

confidence: 99%

Better Surface Integrity and Tribological Properties of Steel Sintered by Powder Metallurgy

et al. 2020

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“…There are many parameters affecting surface quality, such as surface roughness (2-D and 3-D surface roughness), surface waviness, surface form, etc. [5,6], among which, surface roughness parameters and the associated functionality are very important for the evaluation of surface integrity and machining quality [7,8] since surface roughness significantly influences the assembly accuracy, fatigue strength, corrosion resistance, and contact stiffness of the parts [9,10]. Consequently, surface roughness becomes an important parameter of concern for engineers during aviation manufacturing [11,12], for instance, in the manufacturing of the assembly interface of an aircraft vertical tail, as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Online Surface Roughness Prediction for Assembly Interfaces of Vertical Tail Integrating Tool Wear under Variable Cutting Parameters

Wang

Zheng

Zhou

2022

Sensors

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Monitoring surface quality during machining has considerable practical significance for the performance of high-value products, particularly for their assembly interfaces. Surface roughness is the most important metric of surface quality. Currently, the research on online surface roughness prediction has several limitations. The effect of tool wear variation on surface roughness is seldom considered in machining. In addition, the deterioration trend of surface roughness and tool wear differs under variable cutting parameters. The prediction models trained under one set of cutting parameters fail when cutting parameters change. Accordingly, to timely monitor the surface quality of assembly interfaces of high-value products, this paper proposes a surface roughness prediction method that considers the tool wear variation under variable cutting parameters. In this method, a stacked autoencoder and long short-term memory network (SAE–LSTM) is designed as the fundamental surface roughness prediction model using tool wear conditions and sensor signals as inputs. The transfer learning strategy is applied to the SAE–LSTM such that the surface roughness online prediction under variable cutting parameters can be realized. Machining experiments for the assembly interface (using Ti6Al4V as material) of an aircraft’s vertical tail are conducted, and monitoring data are used to validate the proposed method. Ablation studies are implemented to evaluate the key modules of the proposed model. The experimental results show that the proposed method outperforms other models and is capable of tracking the true surface roughness with time. Specifically, the minimum values of the root mean square error and mean absolute percentage error of the prediction results after transfer learning are 0.027 μm and 1.56%, respectively.

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“…It is well known that the machining surface integrity influences strongly the fatigue lifetime of materials, since fatigue micro-cracks initiate always at the surface [12][13][14][15][16][17]. For this reason, several studies have been dedicated to the effects of milling on fatigue behaviour of many materials, particularly aluminium and titanium alloys, and superalloys widely used to manufacture structural parts for aviation and aerospace industries [18][19][20][21][22][23][24][25]. It was proved that residual stresses and surface roughness, particularly, could affect considerably the performance of the milled materials under high cyclic fatigue (HCF) load.…”

Section: Introductionmentioning

confidence: 99%

Influences of up-milling and down-milling on surface integrity and fatigue strength of X160CrMoV12 steel

Laamouri

Ghanem

Braham

et al. 2019

Int J Adv Manuf Technol

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This is an author-deposited version published in: https://sam.ensam.eu Handle ID: .http://hdl.handle.net/10985/18458 To cite this version :Adnen LAAMOURI, Farhat GHANEM, Chedly BRAHAM, Habib SIDHOM -Influences of up-milling and down-milling on surface integrity and fatigue strength of X160CrMoV12 steel Abstract This paper aims to compare the influences of the two peripheral milling modes, up-milling and down-milling, on surface integrity and fatigue strength of X160CrMoV12 high-alloy steel. The experimental investigations showed an important difference between integrity of both milled surfaces. The down-milled surface is lowly work-hardened and well finished (lower roughness), but subjected to tensile residual stresses and severely damaged by folds of metal and short micro-cracks. The up-milled surface is highly work-hardened and subjected to compressive residual stresses, but poorly finished (higher roughness) and damaged by a density of micro-cavities due to carbide extraction. The results of 3-point bending fatigue tests revealed that the fatigue limit at 2 × 10 6 cycles of the up-milled state is largely higher of about 26% in comparison with the down-milled state. The effects of surface integrity induced by each milling mode on fatigue strength were evaluated using a HCF behaviour predictive approach based on Dang Van's multiaxial criterion. The predictive results estimated that the pre-existing micro-cracks play a dominant role in the fatigue strength degradation of the down-milled surface while the other surface effects seem to be lower. On the contrary, the fatigue strength of the up-milled surface is less affected by the pre-existing micro-cavities. The detrimental roughness effect (stress concentration effect) is significantly reduced by the beneficial effects of superficial hardening and compressive residual stresses. So, this study revealed that up-milling is the more appropriate mode for a better surface integrity towards fatigue strength of X160CrMoV12 steel than the down-milling mode.

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Influences of milling and grinding on machined surface roughness and fatigue behavior of GH4169 superalloy workpieces

Cited by 58 publications

References 14 publications

Better Surface Integrity and Tribological Properties of Steel Sintered by Powder Metallurgy

Better Surface Integrity and Tribological Properties of Steel Sintered by Powder Metallurgy

Online Surface Roughness Prediction for Assembly Interfaces of Vertical Tail Integrating Tool Wear under Variable Cutting Parameters

Influences of up-milling and down-milling on surface integrity and fatigue strength of X160CrMoV12 steel

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