Development of a Constitutive Model for Friction in Bulk Metal Forming

Lüchinger, Marco; Velkavrh, Igor; Kern, Kerstin; Baumgartner, Michael; Klien, Stefan; Diem, Alexander; Schreiner, Michael; Tillmann, Wolfgang

doi:10.3390/lubricants6020042

Cited by 8 publications

(7 citation statements)

References 26 publications

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“…The purpose of using lubricants is to reduce the energy losses necessary to overcome friction and reduce the intensity of tool wear [ 10 , 11 ]. During the deformation process, the lubricant influences the change of surface topography of the workpiece, the character of flow of the deformed metal, decreases unit pressure and the coefficient of friction (COF), and also improves the quality of the product surface [ 12 , 13 , 14 ]. Increasing the efficiency of lubrication in the SMF can be obtained by texturing the tool surface, thus creating so-called ‘oil pockets’, which are a reservoir for the lubricant.…”

Section: Introductionmentioning

confidence: 99%

Tribological Performance of Environmentally Friendly Bio-Degradable Lubricants Based on a Combination of Boric Acid and Bio-Based Oils

Trzepieciński

2020

Materials

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Finding effective and environmentally friendly lubrication to use in sheet metal forming operations presents a substantial environmental and economic challenge to the automotive industry. This paper examines the effectiveness of different lubricants in the reduction of the coefficient of friction (COF) in the process of sheet metal forming of the low carbon steel sheets. These lubricants are based on a combination of boric acid (H3BO3) and edible vegetable oils, both of which are natural and environmentally friendly. To evaluate the friction characteristics of the lubricants in a forming operation, a strip drawing friction test is used. This test consisted in drawing a specimen in the form of a sheet metal strip between two non-rotating counter-samples with radii of 200 and 10 mm. The effectiveness of environmentally friendly lubricants in reducing the COF was compared to the traditional petroleum-based lubricants which are used in sheet metal-forming operations. The effect of lubricant conditions and tool surface roughness on the value of COFs is studied. It was found that palm oil in both configurations of countersample radius, both as pure oil and with the addition of 5 wt.% of H3BO3, was the most effective in lowering the coefficient of friction. In most of the conditions analysed, the addition of boric acid into vegetable oils leads to an increase in the lubrication efficiency by up to 15% compared to pure oils. The effectiveness of lubrication by olive and rapeseed oils in decreasing the frictional resistances clearly depends on the nominal pressure applied.

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Section: Introductionmentioning

confidence: 99%

Tribological Performance of Environmentally Friendly Bio-Degradable Lubricants Based on a Combination of Boric Acid and Bio-Based Oils

Trzepieciński

2020

Materials

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“…17(b) [76]. An empirically-based friction model describes friction as a function of the sliding distance and the most relevant friction influencing parameters [77]. In general, to create the friction model, parameters related to galling are always introduced.…”

Section: Friction Models and Gallingmentioning

confidence: 99%

Galling phenomena in metal forming

Dohda

Yamamoto

et al. 2020

Friction

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Galling phenomena in metal forming not only affect the quality of the engineered surfaces but also the success or failure of the manufacturing operation itself. This paper reviews the different galling conditions in sheet and bulk metal forming processes along with their evolution and the effects of temperature on galling. A group of anti-galling methods employed to prevent galling defects are also presented in detail. The techniques for quantitatively measuring galling are introduced, and the related prediction models, including friction, wear, and galling growth models, are presented to better understand the underlying phenomena. Galling phenomena in other processes similar to those occurring in metal forming are also examined to suggest different ways of further studying galling in metal forming. Finally, future research directions for the study of galling in metal forming are suggested.

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“…However, the results obtained show that the analytical model appears to be more suitable than the regression model for the determination of the COF. Lüchinger [ 32 ] successfully determined an optimal friction model for bulk metal forming using stepwise nonlinear regression. Kumar and Kumaraswamidhas [ 33 ] have applied ANOVA to obtain the most significant parameter of AA 6061 composites subjected to the pin-on-disk tribological test.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Friction Phenomena of Ti-6Al-4V Sheets Based on Backward Elimination Regression and Multi-Layer Artificial Neural Networks

2021

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This paper presents the application of multi-layer artificial neural networks (ANNs) and backward elimination regression for the prediction of values of the coefficient of friction (COF) of Ti-6Al-4V titanium alloy sheets. The results of the strip drawing test were used as data for the training networks. The strip drawing test was carried out under conditions of variable load and variable friction. Selected types of synthetic oils and environmentally friendly bio-degradable lubricants were used in the tests. ANN models were conducted for different network architectures and training methods: the quasi-Newton, Levenberg-Marquardt and back propagation. The values of root mean square (RMS) error and determination coefficient were adopted as evaluation criteria for ANNs. The minimum value of the RMS error for the training set (RMS = 0.0982) and the validation set (RMS = 0.1493) with the highest value of correlation coefficient (R2 = 0.91) was observed for a multi-layer network with eight neurons in the hidden layer trained using the quasi-Newton algorithm. As a result of the non-linear relationship between clamping and friction force, the value of the COF decreased with increasing load. The regression model F-value of 22.13 implies that the model with R2 = 0.6975 is significant. There is only a 0.01% chance that an F-value this large could occur due to noise.

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Development of a Constitutive Model for Friction in Bulk Metal Forming

Cited by 8 publications

References 26 publications

Tribological Performance of Environmentally Friendly Bio-Degradable Lubricants Based on a Combination of Boric Acid and Bio-Based Oils

Tribological Performance of Environmentally Friendly Bio-Degradable Lubricants Based on a Combination of Boric Acid and Bio-Based Oils

Galling phenomena in metal forming

Modeling of Friction Phenomena of Ti-6Al-4V Sheets Based on Backward Elimination Regression and Multi-Layer Artificial Neural Networks

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