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

Tomasz Trzepieciński,Marcin Szpunar,Ľuboš Kaščák

doi:10.3390/ma14102570

Abstract

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.

Highlights

Sheet metal forming (SMF) is a process by which sheet metal parts are subjected to geometric change without material reduction
Increasing the load during the strip drawing test causes a clear tendency to reduce the coefficient of friction (Figure 3)
Despite the above-mentioned difficulties in the interpretation of the coefficient of friction (COF), the strip drawing test is a primary method for determination of the COF in SMF [52,68,69,70]

Summary

Introduction

Sheet metal forming (SMF) is a process by which sheet metal parts are subjected to geometric change without material reduction. The process creates a force that causes the material to deform. There are phenomena in the contact zone that are impacted by many variables, such as the macro- and microgeometry of the contact surfaces, pressure, processing temperature, type and viscosity of the lubrication used, die structure, topography and physicochemical phenomena of the contact surfaces, and load dynamics [4,5,6]. The coefficient of friction is primarily determined by the roughness of the surface as well as the structure of the surface layer and its composition [11,12]. The value of the coefficient of friction (COF) is a variable value, and it depends on, among other factors, the pressure force applied [13]. In the case of the Grade 5 titanium alloy (Ti-6Al-4V) studied in this paper, the tribological properties of this material are affected by the processing method, and by the distribution of the mixed crystal system α and β [14] and the content of the alloying elements aluminum and vanadium [15,16]

Methods

Results

Conclusion