The Effect of the Use of Technological Lubricants Based on Vegetable Oils on the Process of Titanium Sheet Metal Forming

Więckowski, W.; Dyja, K.

doi:10.1515/amm-2017-0070

Cited by 10 publications

(9 citation statements)

References 7 publications

(8 reference statements)

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“…However, they can not be used as lubricants if high load magnitudes are applied during forming process (Syahrullaila et al, 2013). The usefulness edible oils (rape-seed oil, olive oil, sunflower oil) has been confirmed by Więckowski & Dyja (2017) in the process of Grade 2 titanium sheet metal forming. In the face of the growing food crisis, more emphasis should be placed on non-edible oils of vegetable origin.…”

Section: Test Proceduresmentioning

confidence: 87%

Assessment of the Tribological Performance of Bio-Based Lubricants Using Analysis of Variance

Szewczyk

Szwajka

2023

AMME

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The purpose of this article is to determine the coefficient of friction of a DC04 steel sheet using a specially designed flat-die strip drawing test. Four different bio-based lubricants, edible (sunflower and rape-seed) and non-edible (karanja and moringa) were used in the study. The experiments were carried out for different contact pressure values. The as‐received specimens were pre‐strained with strains of 7, 14, and 21%. The values of the coefficient of friction as a ratio of the friction force to the normal force were determined. The influence of the viscosity of the lubricant and the contact pressure on the value of the coefficient of friction has been investigated using ANOVA. A tendency to a decrease in the coefficient of friction with increasing contact pressure was observed. Significance results obtained after the ANOVA analysis confirmed the influence of normal pressure and oil viscosity on the value of the coefficient of friction. At the same time, the hypothesis about the influence of the sheet pre-straining on the value of the coefficient of friction was not confirmed by the significant interactions.

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Section: Test Proceduresmentioning

confidence: 87%

Assessment of the Tribological Performance of Bio-Based Lubricants Using Analysis of Variance

Szewczyk

Szwajka

2023

AMME

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“…Determining such a dependence without analysis of variance would be practically impossible. Moreover, nominal load is a parameter that directly affects the value of the friction coefficient, even more so than the lubrication conditions [ 15 , 19 , 24 , 25 ]. The explained variable was the value of the COF.…”

Section: Methodsmentioning

confidence: 99%

“…Vegetable-based lubricants have exclusive properties, such as a high viscosity index and flash point, high lubricity, low evaporation rate and polar nature [ 17 , 18 ]. One of the most important physicochemical properties of lubricants is their wettability, which determines the intensity of lubricant absorption on the surface of the material formed or on a tool [ 19 , 20 ]. Vegetable oils offer 95% biodegradability, which helps in reducing the cost of disposal [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Polynomial Multiple Regression Analysis of the Lubrication Effectiveness of Deep Drawing Quality Steel Sheets by Eco-Friendly Vegetable Oils

Trzepieciński

2022

Materials

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Ensuring adequate lubrication is a key task in the sheet metal forming process. The replacement of commonly used synthetic lubricants in metal forming operations by eco-friendly equivalents is a way to introduce sustainable manufacturing. In this paper, six kinds of vegetable oils (linseed, palm, sunflower, cotton seed, soybean and coconut) were used to study the effect of lubricant type on the value of the coefficient of friction (COF) in sheet metal forming. The strip drawing test was used to simulate the friction conditions. The tests were carried out for various lubrication conditions and pressures. The polynomial quadratic regression model was used to determine the relationship between the input variables (test conditions) and the COF. For the range of the nominal pressures considered (2–12 MPa), the following oils provided the highest lubrication efficiency: palm, sunflower and cotton seed. These oils decreased the value of the COF by about 11–16% depending on the nominal pressure. Linseed oil had the most unfavourable properties, reducing the COF by about 7–12%. For the whole range of pressures considered, the increase in the viscosity of the oil caused a reduction in the value of the COF. The effect of oil density on the COF value was similar. The most unfavourable friction conditions occurred when there was low density and low viscosity of the oil at the same time.

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“…Oils were selected based on the suggestions included in the literature [ 24 , 53 , 54 ]. The selection also took into account the low cost of these oils and their general availability, and the fact that interest had been shown in their potential for reducing the friction coefficient of titanium sheets [ 55 , 56 ]. Table 1 presents the basic physico-chemical properties of the tested oils.…”

Section: Methodsmentioning

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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The Effect of the Use of Technological Lubricants Based on Vegetable Oils on the Process of Titanium Sheet Metal Forming

Cited by 10 publications

References 7 publications

Assessment of the Tribological Performance of Bio-Based Lubricants Using Analysis of Variance

Assessment of the Tribological Performance of Bio-Based Lubricants Using Analysis of Variance

Polynomial Multiple Regression Analysis of the Lubrication Effectiveness of Deep Drawing Quality Steel Sheets by Eco-Friendly Vegetable Oils

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

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