Surface Finish of Cold Rolled Aluminium Foils

Surface Finish of Cold Rolled Aluminium Foil

HR Le and MPF Sutcliffe

Cambridge University Engineering Department, Trumpington Street,
Cambridge, CB2 1PZ, U.K.

ABSTRACT

This paper describes a detailed analysis of the surface finish of aluminium foil which has been cold rolled under industrial conditions in the mixed lubrication regime. Foil stock was rolled with freshly ground rolls at constant speed for the first pass and at a wide range of speed for the second pass. Strip samples were collected after the second pass. For comparison, samples were also collected after rolling with worn rolls. Surface replicas of the rolls were taken with surface replicating tape.

The surface roughness of the strip samples and roll surface replicas was measured with a three-dimensional non-contact interferometric profilometer. The spectrum of the surface roughness was analysed by the Fast Fourier Transform method to identify the way in which different wavelengths of roughness behave. Theory suggests that longer wavelengths of roughness should be crushed more easily. This was confirmed by results on the first pass. A new image analysis technique has been developed to identify and quantify the area of the hydrodynamic pockets. To differentiate between these pits and grind marks transferred from the rolls, the height information was first averaged in the rolling direction and this mean height, which represents the contribution from the grind marks, was subtracted off. Results showed a significant increase in hydrodynamic pitting on the surface with increasing rolling speed.

Key words: roughness, surface finish, surface spectrum, hydrodynamic pitting, mixed regime, lubrication and metal rolling

For presentation at the IOM Conference on Modelling of Metal Rolling Process, London, 13-15 December 1999

1. INTRODUCTION

Modelling of metal rolling process is currently an active theme of research since better understanding can have a significant economic impact due to the high tonnage of metal rolled. Particular interest has been arisen in modelling friction and modification of surface roughness, both to improve product quality and mill productivity.

Friction and the surface quality of the rolled strip is closely related to the amount of oil drawn into the bite [1]. The lubrication regime can be characterised by s, the ratio of the lubricant film thickness hw to the combined surface roughness on the strip and roll, . The film thickness hw can be estimated, using the results of Wilson and Walowit for smooth rolls and strip [3] as,

,(1)

where is the average entraining velocity, is the inlet angle between the strip and roll and Y is the plain strain yield strength of the strip.  is the viscosity of the lubricant at ambient pressure and  is the oil's pressure viscosity coefficient. For thick oil films with s greater than about 1, surface roughening occurs due to the unconstrained deformation of different grains [1]. The resulting poor surface quality is unacceptable for most products. To achieve an appropriate surface finish, rolling must operate in the mixed lubrication regime, where the oil film thickness is smaller than the surface roughness. In this regime asperities on the strip are flattened and tend to conform to the bright surface finish of the rolls. Measurements of friction coefficients in mixed regime on an experimental mill by Tabary et al [2] confirmed that friction coefficient is correlated with s.

Recent measurements of surface roughness in mixed lubrication regime on an experimental mill [4] interpreted the modification of surface roughness by examining the surface spectrum. It is shown that short wavelength components persist more than the long wavelength components. This is confirmed by a new model of surface flattening [5], in which the surface roughness was modelled as two wavelengths with a short wavelength superimposed on a long wavelength component.

The purpose of this paper is to look at the details of the surface of aluminium foils rolled under industrial conditions, to confirm the results of the laboratory-scale tests and to provide benchmarks for the theoretical models currently being developed. The spectral analysis of surface roughness described in [6] is used to analyse the surfaces. A recent method of identifying hydrodynamic pits on cold rolled stainless steel [7] is modified to be appropriate for cold rolled aluminium strips.

Section 2 of this paper describes the details of the strip samples and measurements of surface roughness. The methodology of spectral and hydrodynamic pit analysis is described in section 3. Section 4 presents the results and conclusions are given in section 5.

2. EXPERIMENTAL PROCEDURE

2.1 Collection of samples

A coil of 1200 aluminium alloy foil stock of thickness 0.4 mm was rolled at constant speed for the first pass and at a wide range of speeds for the second pass using freshly ground rolls. The reduction in strip thickness during both passes was approximately 50 percent. Lubricant was applied on both sides of the strip abundantly. Samples of the foil stock was collected from the end of the coil. A sample after the first pass was taken from a region where the coil was being rolled at speed. Changes in speed during the second pass were marked on the side of the coil. These were used to identify the rolling speed of samples which were collected from the middle of the coil, which was scrapped after this pass. Samples rolled with worn rolls under similar conditions were collected for comparison. Replicas of the roll surface were taken before the second pass using Press-O-Film surface-replicating tape supplied by Testex.

2.2 Measurements of surface roughness

Surface roughness was measured in a Zygo non-contacting 3-D interferometric profilometer. The equipment has a lateral resolution of 0.5 m and vertical resolution of 0.1 nm.

Preparation of samples

It is very important to use flat samples, a problem that is especially relevant for thin foils and the replica tape. To ensure this, the samples are carefully cut, trimmed and stuck onto a glass slide. The surface of the strip samples were cleaned with acetone to remove residual lubricant before measurements were taken.

Measurements

A 20 objective lens (giving an overall magnification of 200) was used to ensure that the field of view (0.710.53 mm) and depth of field (3.5 µm) is sufficient to take in the relevant surface features. The lateral sampling distance is 2.2 µm. Normally ten areas are measured and averaged to give the average roughness and standard error. Details of the measurements are listed in Table I.

Table I Details of the measurements

Magnification / Field of view (mm) / Depth of view (m) / Sampling distance (m)
200 / 0.710.53 / 3.5 / 2.2
400 / 0.350.26 / 3.5 / 1.1

?? Which of these two lines is relevant - if only one is relevant, I think it should be put in the text instead, as indicated above.

1. ANALYSIS

3.1 Spectrum analysis

The surface of cold rolled aluminium foil contains roll marks and hydrodynamic pits. Roll marks, running longitudinally in the rolling direction, are usually the dominant features. To analyse the surfaces, two dimensional arrays of surface heights are exported from the profilometer to a computer for analysis in Matlab. The columns of the array correspond to changes in surface height in the rolling direction and the rows correspond to the transverse direction. For a given one-dimensional discrete data array of the surface heights, the single sided power spectral density S(1/) can be found using a Fast Fourier Transformation [8, 9] with a Hanning window [10]. S(1/) represents the contribution to the variance of heights of the component with wavelength . Therefore the contribution between wavelengths  and  is given by

(1)

Taking a fixed upper cut-off at the value of 200 m ?? you have 200 here and 250µm in the next line?? to eliminate waviness in the strip, 2()=s2(, 250m) represents a cumulative roughness variance including all wavelength greater than . For each row of data the one-dimensional FFT is used to find the spectrum of the surface roughness across the rolling direction. Spectra for all the rows in the measured area are averaged to give an average spectral density across the rolling direction and corresponding cumulative variance s2.

3.2 Hydrodynamic pitting

Although the surface roughness is mainly characterised by longitudinal roll marks, small hydrodynamic pits become more prevalent at high rolling speeds. To identify these features, roll marks are first identified using a straight line least-squares fit to each column of data in the rolling direction. These roll marks are then subtracted from the height array. Although this removes most of the roughness associated with the roll marks, some undulations are left. Therefore, it is not accurate to identify the pits by a straightforward analysis taking those regions below some cut-off height. Instead, the pits are located in two ways. Since the hydrodynamic pits have large slopes in the rolling direction, as compared with any furrows associated with roll marks, areas can be identified as pits if the magnitude of the slope in the rolling direction is greater than three times the mean slope of the strip in the rolling direction. Nevertheless, the bottoms of very large pits may not be detected using this criterion. These areas are found by identifying those regions where the depth of the pit is greater than twice the r.m.s. height of the strip. Note that, in making this comparison, the pit slope and depth are taken from the surface data after eliminating the roll marks, while the mean slope and r.m.s. height of the sample are taken from the original profile including roll marks. ?? is this right?? The fraction of pitting area is quantified by dividing the total pixel area by the pixel area of the pits. Further details of this procedure and a sensitivity analysis are given in [7].

4RESULTS

4.1Roughness amplitude

The r.m.s. surface roughness of the foil stock and foil samples taken after the first and second passes is shown in Fig. 1a. The roll roughness r is indicated by an arrow on the graph. Each point represents an average of ten measurements. Error bars indicate the standard deviation of measurements within this sample. The results show that the roughness on the bottom surface of the foil stock is significantly greater than on the top surface. Nevertheless, both sides of the surface have nearly conformed to the roll surface after the first pass, so that the difference between the two sides is then negligible. In the second pass, the surface roughness is slightly further reduced. The high degree to which the strip conforms to the roll surface reflects the small value of lubrication parameter s, which is about ? for the first pass and varies between ? and ? for the second pass.

Figure 1b shows the effect of rolling speed on the r.m.s. surface roughness after the second pass. Since the surface roughness on both the incoming and outgoing strip is close to that of the rolls, any effect of speed on surface roughness is overshadowed by scatter in the measurements. Nevertheless, there appears to be a slight increase in the surface roughness at very low speeds which may be associated with a breakdown of lubrication and associated heat-banding observed on the strip.

4.2Surface spectrum

Figure 2 illustrates the change in surface spectrum from fresh to worn rolls. Figure 2a plots the spectral density and Fig. 2b plots the cumulative variance, normalised by the r.m.s. roughness of each roll replica. Figure 2a shows that short wavelength components are most rapidly reduced in amplitude as the roll wears. The way in which the roll surface imprints on the strip surface can be seen from the change in shape of the curves, Fig. 2b. The relative contribution from wavelengths shorter than 5µm (1/ > 200 mm-1), given by the difference between one and the cumulative variance at this frequency, is significantly greater for the strip rolled by a fresh roll than for the strip from the worn rolls, reflecting the reduction in short wavelength components as the rolls wear.

Figure 3 shows the change in the surface spectrum during the pass schedule. The contribution of long wavelength components to the surface amplitude falls through the pass schedule as these components are crushed more rapidly than the short wavelength components. This confirms the results of laboratory experiments [4] and predictions from theory [5]. Although the surface of the strip after the first pass has nearly conformed to the roll surface, Fig. 3b shows that there is a slight further change in the relative contributions of long and short wavelength components during the second pass, as the long wavelengths continue to be crushed more readily. Figure 3b shows that, for the second pass, there is no significant effect of rolling speed on the surface spectra. By this pass the actual changes in roughness are slight, and the differences in hydrodynamic entrainment of oil at these small values of s is not having a sufficiently large influence on the crushing process to be detectable.

4.3Variation of hydrodynamic pits

Figure 4 shows the surface maps and the results of the hydrodynamic pit analysis for the foil stock samples. The height of the surface is indicated by the grey scale. Figure 4b shows how the analysis successfully separates hydrodynamic pits from the roll marks. Figure 5 shows similar surface height and pit analysis maps for a sample taken after the first pass. Both the area of pits and their size are reduced slightly by the first pass. Figures 6a and 6b show the results of the pitting analysis for samples after the second pass, at a low and high speed respectively, showing how the pitting area increases with rolling speed. The fraction of pitting area is quantified and plotted against pass number in Fig. 7a and against rolling speed in Fig. 7b. Results show how the pitting area is reduced during the schedule. The pitting area has a very good correlation with the rolling speed in the second pass, showing an increase in pit area with an increase in rolling speed, presumably due to the hydrodynamic action.

5CONCLUSIONS

(1)Surface roughness measurements on aluminium foil rolled under industrial conditions show that the surface of the strip nearly conforms to the roll surface after the first pass. Subsequent passes slightly reduce the surface roughness on the strip.

(2)Spectral analysis confirms the results of laboratory-scale trials, that long wavelength components on the strip surface are flattened more rapidly than short wavelength components.

(3)A program has been developed which successfully recognises the hydrodynamic pits on the strip surface. Results show that both the area and size of hydrodynamic pits are reduced during rolling. Pits are eliminated more effectively during the second pass at lower rolling speeds.

ACKNOWLEDGEMENTS

The authors wish to thank K. Waterson, D. Miller (Alcan Int. Ltd.), P. Reeve and C. Fryer (Alstom) and all the personnel at Alcan Glasgow for their help with the trials. The authors are obliged to R. Ahmed for his help with the hydrodynamic pitting analysis. The financial support from EPSRC, Alcan Int. Ltd. and Alstom is greatly acknowledged.

REFERENCES

1. Schey JA, “Surface Roughness Effects in Metalworking Lubrication”, Lubrication Engineering, 39, (1981) 376-382.
2. Tabary PT, Sutcliffe MPF, Porral F and Deneuville P, “Measurements of friction in cold metal rolling”, ASME J. Tribology, 118, (1996) 629-636.
3. Wilson WRD and Walowit JA, “An Isothermal Hydrodynamic Lubrication Theory for Strip Rolling With Front and Back Tension”, Proc. 1971 Tribology Convention, I. Mech. E., London, (1972) 164-172.
4. Sutcliffe MPF and Le HR, “Measurements of surface roughness in cold metal rolling in mixed lubrication regime”, To be published in STLE Tribology Transactions (1999).

5.Le HR and Sutcliffe MPF, “A Two-Wavelength Model of Surface Flattening in Cold Metal Rolling with Mixed Lubrication”, Submitted to STLE/ASME International Tribology Conference, February 1999.

1. Sutcliffe MPF, “Flattening of random rough surfaces in metal forming”, To appear in ASME J. Tribology, 1999.
2. Ahmed R and Sutcliffe MPF, “Identification of surface features on cold rolled stainless steel strip”, Document in preparation for submission to Wear, 1999.
3. Moalie H, Fitzpatrick JA and Torrance AA, “A spectral approach to the analysis of rough surfaces”, ASME J. Tribology, 111, (1989) 359-363.
4. Ju Y and Farris TN, “ Spectral analysis of two-dimensional contact problems”, ASME J. Tribology, 118(2), (1996) 320-328.
5. Matlab, The Mathworks Inc., (1994).

Nomenclature

hwsmooth film thickness using the Wilson and Walowit formula

s2(1, 2)surface variance of the wavelength between 1 and 2

S single sided power spectral density

average entraining velocity

Y plane strain yield stress of the strip

oil viscosity pressure index

0 inlet angle between the strip and roll (in radians)

oil viscosity at ambient pressure

wavelength of the surface spectrum

rr.m.s. surface roughness on the rolls

sr.m.s. surface roughness on the strip

tcombined r.m.s. surface roughness of the strip and roll

2 ()variance of all wavelengths greater than 

These figure captions to replace the existing ones, please.

Fig. 1. R.m.s. roughness amplitude of strip samples, (a) Change during the pass schedule,
(b) The effect of rolling speed during the second pass.

Fig. 2. The effect of roll roughness on strip surface spectrum, (a) Spectral density,
(b) Cumulative surface variance, normalised by the strip roughness variance.

Fig. 3. The change in the strip surface spectrum during rolling, (a) Spectral density,
(b) Cumulative surface variance, normalised by the strip roughness variance.

Fig. 4. Surface maps of the foil stock, (a) Surface heights, (b) Pitting analysis.

Fig. 5. Surface maps of the foil after the first pass, (a) Surface heights, (b) Pitting analysis.

Fig. 6. The effect of rolling speed on pitting during the second pass,
(a) Rolling speed of 106 mpm, (b) Rolling speed of 608 mpm.

Fig. 7. Pit area of strip samples, (a) Change during the pass schedule,
(b) The effect of rolling speed during the second pass.

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