The Interaction between the Sheet/Tool Surface Texture and the Friction/Galling Behaviour on Aluminium Deep Drawing Operations

The increasing demands for lightweight design in the transport industry have led to an extensive use of lightweight materials such as aluminium alloys. The forming of aluminium sheets however presents significant challenges due to the low formability and the increased susceptibility to galling. The use of tailored workpieces and controlled die roughness surfaces are common strategies to improve the tribological behaviour, whilst galling is still not well understood. This work is aimed at analysing the interplay between the sheet and tool surface roughness on the friction and galling performance. Different degrees of Electro Discharge Texturing (EDT) textures were generated in AA1050 material strips, and tooling presenting different polishing degrees were prepared. Strip drawing tests were carried out to model the tribological condition and results were corroborated through cup drawing tests. A new galling severity index (GSI) is presented for a quick and quantitative determination of both galling occurrence and severity. The present study underlines the key role of die topography and the potential of die surface functionalization for galling prevention.

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

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.

Higher Productivity In Forming High-alloyed Steel By Temperature Insensitive Friction Behavior

Like in many other production technologies, a broad process window for metal forming is desired. The goal is always a stable process chain. One of the key aspects for metal forming are stable tribological conditions. Instabilities can be caused by, amongst others, different material batches, change in temperature during the production process, different lubricant amounts and different stroke rates. At the beginning of a production run, the tribological stability suffers from transient temperature effects caused by plastic and frictional work and a viscosity drop of the lubricant. To control the tribology, different strategies are suitable: changing the oil type, the oil amount, the blank holder force or the stroke rate. Within the EU-project ASPECT, control strategies on blank holder forces are developed as well as lubricants with improved stability on their behaviour as a function of temperature. This paper will focus on the latter. In preliminary ball on plate test the friction and wear of lubricant formulations were investigated and compared to a Reference lubricant. Followed by strip drawing and forming tests. Finally, the concept is proven in trials on a demonstrator line, which is close to serial production.

Temperature induced friction increase in friction test and forming demonstrator for sheet metal forming

High process stability is needed in sheet metal forming industry. This can be achieved by predicting and controlling the transient process and temperature variation, especially at start of production. In this connection, the temperature induced friction changing plays a significant role because it leads to product failures. The handling of the transient friction effects is currently done reactively, based on the individual experience of the machine operators. In future, those transient effects need to be controlled. This paper shows initially an analysis of the temperature induced friction increase in a well-known and proven flat strip drawing test. Different tribological systems were tested at tool temperatures between 20 and 80 °C. The temperature increase results in a higher friction of up to 77 %. Several influences on friction increase will be presented. These friction influences were verified afterwards with a heated forming demonstrator under laboratory conditions.

Strain Induced Surface Change in Sheet Metal Forming: Numerical Prediction, Influence on Friction and Tool Wear

In sheet metal forming, free deformation of the sheet takes place frequently without contact with forming tools. The pre-straining resulting from the free deformation leads to a surface roughening of the sheet metal. It is assumed that the roughening has an influence on friction and wear behavior of the following forming process as well as the painting quality after the manufacturing. In this paper, a numerical prediction based on a polycrystalline model is first proposed to predict the effect of surface roughing based on the material data of the as-received state of the sheet metal. Different states of strain are analyzed and the numerical result is validated through experimental evaluation. Besides the numerical prediction, the friction behavior after pre-straining is evaluated in strip drawing tests and the coefficient of friction (COF) is calculated. For interpretation of the measured COF, the surface roughness after the friction test and the surface image are evaluated by a transparent toolset. It is shown that the surface transformation as a result of pre-straining has a negative influence on the lubricating effect of the sheet metal and degrades the friction behavior. Finally, the influence of the strain-induced surface roughening on wear is discussed based on wear testing in strip drawing test with draw bead geometry.

Experimental Assessment of Friction Coefficient in Deep Drawing and Its Verification by Numerical Simulation

The friction coefficient in the simulation of stamping processes should be defined. Modern simulation software allows its definition as constant or its dependence on pressure or temperature. It is also useful in stamping processes to define different values in different regions, as it often reflects the nature of deformation process. This article deals with the regression and analytical models commonly used to determine the friction coefficients in specified areas of the stamping process. Analytical models were verified by an experimental strip drawing test under the same contact conditions. Steel sheets for the automotive industry were used in experiments and simulations—extra deep drawing quality DC 05 and austenitic stainless steel AISI 304. Friction coefficients were also evaluated when the cup test was performed. A regression model of drawing to the blankholding force was applied to the results. Conformity of friction coefficients when measured by cup tests and strip tests was confirmed. The values of the friction coefficient reached from the experiment were applied in FEM simulation software.