Abstract
The aim of the research presented in this article was to determine the value of the friction coefficient using a simple tribological test and to build an empirical model of friction with the use of radial basis function artifi-cial neural networks. The friction tests were carried out on a specially designed friction simulator that allows a sheet metal strip to be drawn between two fixed dies. The test materials were sheets of Ti-6Al-4V titanium alloy with a thickness of 0.5 mm. The friction tests were carried out with variable contact forces of counter-samples with rounded surfaces and in various lubrication conditions. Mineral oils and bio-degradable oils with the addition of boric acid (5 wt %) were tested. Based on the results of friction investigations, neural models of friction were built using RBF artificial neural networks. The good properties of the RBF network 2:2-35-1:1 were confirmed by a high value of the determination coefficient R2 = 0.9984 and a low value of the S.D. ratio equal to 0.0557. It was found that the COF value was the highest for the average values of both the nominal pressure and kinematic viscosity. Over the entire range of nominal pressures applied, SAE10W-40 engine oil ensured the most effective reduction of the COF. The COF value was the highest for the average values of both the nominal pressure and kinematic viscosity.
Highlights
Sheet metal forming (SMF) is one of the most popular methods of obtaining finished products, especially in the automotive industry
The processes taking place in the contact zone in SMF are influenced by many factors, including the amount of normal pressures, the macro- and microgeometry of the contact interface, both the type and the viscosity of the lubricant, the kind of die and workpiece material, the topography of the sheet surface and tools, the dynamics of the loads, physicochemical phenomena on the contact surface and the processing temperature [1, 2]
The frame of the friction simulator was mounted in the bottom grip of the testing machine while one end of the sheet metal strip was mounted in the upper grip of the tensile machine
Summary
Sheet metal forming (SMF) is one of the most popular methods of obtaining finished products, especially in the automotive industry. The factors dependent on the technological parameters of the SMF process include the values of normal pressure and the sliding speed [3, 4]. The value of the coefficient of friction (COF) continuously changes during the forming process due to the flattening and wear of the roughness asperities on the tool surface [4, 5]. Depending on the structure existing at a room temperature, titanium alloys are divided into single-phase α alloys, two-phase α + β and single-phase β alloys. Each group of these alloys is characterised by different mechanical and technological properties. The basic wear mechanism in titanium alloys is abrasion followed by adhesion and transfer layer [8]
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