Tribological effects of chlorine-free lubricant in strip drawing of advanced high strength steel

Jewvattanarak, Phanuwat; Mahayotsanun, Numpon; Mahabunphachai, Sasawat; Ngernbamrung, Sukunthakan; Dohda, Kuniaki

doi:10.1177/1350650115622366

Cited by 6 publications

(5 citation statements)

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“…The countersamples were made from 1.2063 (145Cr6) tool steel. The strip test is a basic test for assessing friction conditions in sheet metal forming [39,40] The developed friction tester consisted of two rounded countersamples ( between which a strip of sheet metal with a width of w = 0.018 m moved durin The upper end of the sample was mounted in the holder of the Zwick/Roell Z1 machine. The normal force was set through a spring with known force-d characteristics (Figure 3).…”

Section: Friction Test Proceduresmentioning

confidence: 99%

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The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

Trzepieciński

2024

Materials

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Friction is one of the main phenomena accompanying sheet metal forming methods, affecting the surface quality of products and the formability of the sheet metal. The most basic and cheapest way to reduce friction is to use lubricants, which should ensure the highest lubrication efficiency and at the same time be environmentally friendly. Due to the trend towards sustainable production, vegetable oils have been used in research as an alternative to petroleum-based lubricants. The analysis of friction in sheet metal forming requires an appropriate tribotester simulating the friction conditions in a specific area of the sheet metal being formed. Research has used a special strip drawing tribometer, enabling the determination the value of the coefficient of friction in the blankholder zone in the deep drawing process. Quantitative analysis of the friction phenomenon is necessary at the stage of designing the technological process and selecting technological parameters, including blankholder pressure. This article presents the results of friction testing of 1.0338 (DC04) steel sheets using a strip drawing test. The experimental tests involved pulling a strip of sheet metal between two countersamples with a rounded surface. The tests were carried out on countersamples with different levels of roughness for the range of contact pressures occurring in the blankholder zone in the deep drawing process (1.7–5 MPa). The values of the coefficient of friction determined under dry friction conditions were compared with the results for edible (corn, sunflower and rapeseed) and non-edible (Moringa, Karanja) vegetable lubricants. The tested oils are the most commonly used vegetable-based biolubricants in metal forming operations. Multi-layer artificial neural networks were used to determine the relationship between the value of the contact pressure, the roughness of the countersamples, the oil viscosity and density, and the value of the coefficient of friction. Rapeseed oil provided the best lubrication efficiency during friction testing for all of the tested samples, with an average surface roughness of Sa 0.44–1.34 μm. At the same time, as the roughness of the countersamples increased, a decrease in lubrication efficiency was observed. The lowest root mean squared error value was observed for the MLP-4-8-1 network trained with the quasi-Newton algorithm. Most of the analysed networks with different architectures trained using the various algorithms showed that the kinematic viscosity of the oil was the most important aspect in assessing the friction of the sheets tested. The influence of kinematic viscosity on the value of the coefficient of friction is strongly dependent on the surface roughness of the countersamples.

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Section: Friction Test Proceduresmentioning

confidence: 99%

“…The countersamples were made from 1.2063 (145Cr6) tool steel. The strip drawing test is a basic test for assessing friction conditions in sheet metal forming [39,40].…”

Section: Friction Test Proceduresmentioning

confidence: 99%

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

Trzepieciński

2024

Materials

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“…Based on the values of the average friction force and the pulling force, the value of the coefficient of friction μ was determined from Eq. ( 1) (Jewvattanarak et al, 2016): Friction tests were carried out under lubrication conditions with hydraulic oil LHL32 (kinematic viscosity 21.9 mm 2 /s, density 874.1 kg/m 3 ), gear oil 75W-85 (kinematic viscosity 64.3 mm 2 /s, density 862.0 kg/m 3 ) and engine oil 10W-40 (kinematic viscosity 97 mm 2 /s, density 870.0 kg/m 3 ). Reference tests were performed for as-received surfaces of sheet metals.…”

Section: Friction Testmentioning

confidence: 99%

Frictional characteristics of EN AW-6082 aluminium alloy sheets used in metal forming

Slota,

Kaščák,

Lăzărescu

2024

AMME

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This article is devoted to testing EN AW-6082 aluminium alloy sheets in friction pair with NC6 (1.2063) tool steel. A special tribometer designed to simulate the friction conditions in sheet metal forming processes was used for friction testing. The research aimed to determine the influence of contact pressure, surface roughness of the tool, and lubrication conditions on the value of the coefficient of friction in the strip drawing test. Three grades of typical petroleum-based lubricants with kinematic viscosities between 21.9 and 97 mm2/s were used in the tests. The surface morphologies of the sheet metal after the friction process were observed using a scanning electron microscope. A tendency for the coefficient of friction to decrease with increasing contact pressure was observed. LHL32 and 75W-85 oils lost their lubricating properties at a certain pressure value and with further increase in pressure, the coefficient of friction value tended to increase. The 10W-40 oil with the highest viscosity reduced the coefficient of friction more intensively than the LHL32 oil.

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“…It was found, in general, that all the vegetable oils (i.e., linseed, rapeseed, sunflower, and palm) with the addition of boric acid were shown to be effective in lowering the COF. Jewvattanarak et al [24] used different lubrication conditions at two sliding speeds (10 and 100 mm/min) to determine the COF of a hot-rolled JSH780R steel sheet. The experimental results revealed that a mixture of chlorine and sulphur additives in the lubricant provided the best adsorption ability for the metal oxides.…”

Section: Introductionmentioning

confidence: 99%

An Investigation into the Friction of Cold-Rolled Low-Carbon DC06 Steel Sheets in Sheet Metal Forming Using Radial Basis Function Neural Networks

Trzepieciński,

Szwajka,

Szewczyk

2023

Applied Sciences

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This article presents the friction test results for cold-rolled low-carbon DC06 steel sheets, which are commonly processed into finished products using sheet metal forming methods. A strip drawing test with flat dies was used in the experimental tests. The strip-drawing test is used to model the friction phenomena in the flange area of the drawpiece. The tests were carried out using a tester that enabled lubrication with a pressurised lubricant. The friction tests were carried out at different nominal pressures, oil pressures, and friction conditions (dry friction and oil lubrication). Oils destined for deep-drawing operations were used as lubricants. Neural networks with radial base functions (RBFs) were used to explore the influence of individual friction parameters on the value of the coefficient of friction (COF). Under lubrication with both oils considered, the value of the COF increased with decreasing oil pressure. This confirms the correctness of the concept of the device for reducing friction in the flange area of the drawpiece. The developed concept of pressurised lubrication is most effective at relatively small nominal pressures of 2–4 MPa. This range of nominal pressures corresponds to the actual nip pressures when forming deep-drawing steel sheets. Under conditions of dry friction, the values obtained for the COF rise above 0.3, while under lubrication conditions, even without pressure-assisted lubrication, the COF does not exceed 0.2. As the nominal pressure increases, the effectiveness of the lubrication exponentially decreases. It was found that the Sq parameter carries the most information regarding the value of the COF. The RBF neural network with nine neurons in the hidden layer (RBF-8-9-1) and containing the Sq parameter as the input was characterised by an R2 of 0.989 and an error of 0.000292 for the testing set.

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Tribological effects of chlorine-free lubricant in strip drawing of advanced high strength steel

Cited by 6 publications

References 45 publications

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet

Frictional characteristics of EN AW-6082 aluminium alloy sheets used in metal forming

An Investigation into the Friction of Cold-Rolled Low-Carbon DC06 Steel Sheets in Sheet Metal Forming Using Radial Basis Function Neural Networks

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