Application of the Finite Element Method to Simulate the Friction Phenomenon in a Strip Drawing Test

Fejkiel, Romuald; Goleń, Patryk

doi:10.7862/rm.2023.5

Cited by 4 publications

(5 citation statements)

References 19 publications

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“…The min-max function (Equation ( 5)) was used to normalise the data, which allowed the values of the input parameters and the output parameter to be transformed into the range [0, 1]. In fact, normalisation modifies the value of the data, but it achieves this while maintaining information about the distance between each point: N = X − x min x max − x min (5) where X is the value of the normalised parameter and x min and x max are minimum and maximum values of the normalised parameter, respectively. The entire training set contained 120 sets of input parameters and the corresponding value of the coefficient of friction.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…This method of plastic working is fast and does not cause production waste, which is inherent in machining processes [4]. The properties of the finished product, such as the surface quality, are mainly influenced by the friction and lubrication conditions [5]. During the deformation process, friction causes a change in the surface topography and material flow character of the deformed workpiece and a deterioration in the surface quality of the product [6,7].…”

Section: Introductionmentioning

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: Artificial Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

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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“…In order to determine the friction and wear of materials, the following types of tests and tribometers may be used: (a) strip drawing test with flat [ 19 , 20 ] and (b) rounded [ 21 ] (c) countersamples, (d) bending-under-tension test [ 22 , 23 ], (e) draw-bead test [ 24 , 25 ], and (f) ball-on-disc [ 26 ], (g) block-on-disc [ 27 ], (h) pin-on-ring [ 28 ], and (i) pin-on-disc tribometers [ 29 , 30 ]. Most of the studies, the results of which can be found in the literature, indicate the susceptibility of aluminium sheets to galling and intensification of the flattening mechanism.…”

Section: Introductionmentioning

confidence: 99%

Friction Behaviour of 6082-T6 Aluminium Alloy Sheets in a Strip Draw Tribological Test

et al. 2023

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Aluminium alloy sheets cause many problems in sheet metal forming processes owing to their tendency to gall the surface of the tool. The paper presents a method for the determination of the kinematic friction coefficient of friction pairs. The determination of coefficient of friction (COF) in sheet metal forming requires specialised devices that ‘simulate’ friction conditions in specific areas of the formed sheet. In this article, the friction behaviour of aluminium alloy sheets was determined using the strip drawing test. The 1-mm-thick 6082 aluminium alloy sheets in T6 temper were used as test material. Different values for nominal pressures (4.38, 6.53, 8.13, 9.47, 10.63, and 11.69 MPa) and different sliding speeds (10 and 20 mm/min.) were considered. The change of friction conditions was also realised with several typical oils (hydraulic oil LHL 32, machine oil LAN 46 and engine oil SAE 5W-40 C3) commonly used in sheet metal forming operations. Friction tests were conducted at room temperature (24 °C). The main tribological mechanisms accompanying friction (adhesion, flattening, ploughing) were identified using a scanning electron microscope (SEM). The influence of the parameters of the friction process on the value of the COF was determined using artificial neural networks. The lowest value of the COF was recorded when lubricating the sheet metal surface with SAE 5W40 C3 engine oil, which is characterised as the most viscous of all tested lubricants. In dry friction conditions, a decreasing trend of the COF with increasing contact pressure was observed. In the whole range of applied contact pressures (4.38–11.69 MPa), the value of the COF during lubrication with SAE 5W40 C3 engine oil was between 0.14 and 0.17 for a sliding speed of 10 mm/min and between 0.13 and 0.16 for a sliding speed of 20 mm/min. The value of the COF during dry friction was between 0.23 and 0.28 for a sliding speed of 10 mm/min and between 0.22 and 0.26 for a sliding speed of 20 mm/min. SEM micrographs revealed that the main friction mechanism of 6082-T6 aluminium alloys sheet in contact with cold-work tool steel flattens surface asperities. The sensitivity analysis of the input parameters on the value of COF revealed that oil viscosity has the greatest impact on the value of the COF, followed by contact pressure and sliding speed.

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“…The model of the surface layer of the tool and workpiece is characterised by several properties that determine the occurrence and participation of individual wear mechanisms (Figure 3). Owing to the subjection of different areas of the tool to nominal pressures and friction conditions, many tests were developed to simulate friction conditions only in selected places of the formed sheet, i.e., strip drawing test [30], a bending under tension test [31] and a draw bead test [32,33].…”

Section: Introductionmentioning

confidence: 99%

Approaches for Preventing Tool Wear in Sheet Metal Forming Processes

Trzepieciński

2023

Machines

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Sheet metal forming processes, the purpose of which is to give the shaped material appropriate mechanical, dimensional and shape properties, are characterised by different values of unit pressures and lubrication conditions. Increasing the efficiency of tool work by increasing their durability, efficiency and reliability is still one of the main indicators of increasing production efficiency. Tool wear in metal forming technologies significantly differs from the character of wear in other methods of metalworking, such as machining. This article presents the characteristics of tool wear mechanisms used in sheet metal forming. Possibilities of increasing the durability of tools by applying coatings produced by laser techniques, chemical vapour deposition and chemical vapour deposition are also discussed. Great emphasis is placed on self-lubricating and functional materials and coatings. Current trends in lubricants and lubrication methods in sheet forming, including tool texturing, are also presented.

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Application of the Finite Element Method to Simulate the Friction Phenomenon in a Strip Drawing Test

Cited by 4 publications

References 19 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

Friction Behaviour of 6082-T6 Aluminium Alloy Sheets in a Strip Draw Tribological Test

Approaches for Preventing Tool Wear in Sheet Metal Forming Processes

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