Continuous drive friction welding (CDFW) is a solid-state process that delivers many benefits, including environment friendliness, being more economical, and a significant reduction in the formation of intermetallic layers. Friction welding was first discovered in 1995 by Thomas
CDFW is generally divided into two stages: a friction stage and a forging stage. The process begins with bringing the two parts to be welded into proximity. One side is attached to a flywheel to rotate at a specific rotational speed (RS) (rotating side). The other is attached to a pressure application apparatus and not allowed to turn (fixed side). The friction stage is the portion of the process where the two surfaces to be welded together are rubbed against each other while one side continuously rotates. The other side is under a constant pre-determined force. The process is carried out for a specific time, depending on the welded material. After the completion of that time, the forging or upset stage is commenced by suddenly stopping the rotation and immediately applying a higher force for a pre-determined time that lasts until the end of the process.
Many studies have focused on CDFW of similar materials, specifically aluminum, and any process modifications that may affect the process. Abdulla
Likewise, studies pertaining to the welding of dissimilar materials have been widely published, especially those that discuss welding steel alloys to aluminum alloys. In Sahin's study [7], austenitic stainless steel was welded to aluminum. Following the conclusion of the welding process, the welded joints were evaluated using statistical procedures, tensile tests, and microhardness tests. Reddy
The most recent research trends in CDFW studies investigated joint properties for metal matrix alloys. Hincapi
High-density polyethylene (HDPE) is a high-diffusion thermoplastic polymer. Polymer materials such as HDPE have many advantages that allow them to be attractive alternative materials, especially in corrosive environments or joint replacement parts. Friction welding of HDPE as either FSW or FSSW has been widely investigated. Gao
A limited number of studies have investigated joining HDPE using CDFW. One study by Hasegawaa
Statistical procedures such as experimental design can prove helpful in processes involving many levels and require design optimization. Some researchers implemented experimental designs to determine significant process parameters or levels or optimize the process. Most statistical experimental design studies consider using Taguchi analysis [10, 20,21,22]. Response surface method (RSM) offers a robust experimental design procedure. The statistical analysis allows for finding the most significant parameters and possible interactions. The resulting response surface plots also allow visualizing the relationship between process parameters and measured responses. Experimental designs of CDFW of polymers have not been widely investigated in the literature. To the authors’ knowledge, there are only a very few RSM investigations available concerning CDFW, and the ones concerning CDFW of HDPE number even fewer.
This paper explores the optimization of CDFW of HDPE using RSM, considering related process parameters and desirable process outcomes. The effect of the welding process parameters on joint quality is investigated. The joint quality assessment employing maximum welding temperature, axial shortening, and TS is reported.
HDPE rods measuring 16 mm in diameter were procured from a local supplier. The properties of the HDPE used are listed in Table 1. The rods were cut into smaller segments (65 mm) to be used for the welding process. The surfaces to be welded were washed with distilled water and dried before the welding operation. CDFW of HDPE was conducted utilizing a lathe machine equipped with a pneumatic system fabricated in the laboratory to control the welding process parameters, as shown in Figure 1. The same setup was used for welding different materials, such as aluminum and steel, as indicated in Tashkandi and Mohamed [5]. Thus the present experimental setup that uses a lathe machine to perform the welding is valid.
Physical and mechanical properties of HDPE [23]
Melting temperature (°C) | 126–135 |
Crystallization temperature (°C) | 111.9 |
Density (g/cm3) | 0.955 |
Thermal conductivity (W/mK) | 0.35–0.49 |
Specific heat – solid (kJ/kg°C) | 1.9 |
Tensile strength (MPa) at 23°C | 23.0–29.5 |
CDFW machine setup. CDFW, continuous drive friction welding
The main parameters that can influence the friction welding procedure are the time of friction, the friction force, the rotating speed, the upset force, and the upset time. Since the literature on CDFW of HDPE is limited, and the ranges of the welding parameters can be very large, a series of trial runs were conducted. The purpose was to narrow the parameter ranges according to the requirements of welding such material. Preliminary results indicated that very high rotating speeds (>1,000 rpm) and very high friction force led to failed joints. Very high RS's or excessive friction force cause wear in the material instead of softening it at temperatures below its melting temperature, thus preventing welding.
The trial-and-error experiments also indicated that the RS's and friction force should be <600 rpm and 2,000 N, respectively. The runs did not reveal any noticeable effects in the joint's quality or appearance caused by the upset force and the upset time. Hence, upset time and force were not considered process parameters investigated in this study and were kept constants for all the study runs.
The process parameters chosen for this work were the time of friction (
Levels of process parameters for CDFW of HDPE
RS (rpm) | Speed | 82 – 169 – 300 – 400 – 550 |
Friction force – |
Force | 1,000–2,000 |
Friction time – |
Time | 30–60 |
The experimental design was a two-level full design, with a total number of runs of 65, consisting of 20 cubic points, 25 center points within the cube, and 20 axial points. It was run in a single block and with a single replication with an alpha level of 1.14. The order of the runs was randomized, and experiments were run according to the randomized order.
The responses used to evaluate the process parameters were the maximum welding temperature recorded during the experiment, the axial shortening, and the joint's TS. The welding flash and axial shortening formation are directly related to the heat generated and the maximum welding temperature. Combining the heat generated, the axial shortening, and TS may be an appropriate technique to identify the range of parameters that influence the welds’ quality and provide an insight into optimal process parameters.
The temperature was measured using an IR Dual Laser Point Thermometer at the contacting surfaces. It had an operational range of −50°C to 800°C, a spatial accuracy of 1 mm, and a time accuracy of 0.5 s. The device can be calibrated according to the emissivity of the measured material. The emissivity was adjusted accordingly, and the thermometer was calibrated successfully before any temperature measurement. The maximum contact temperature was recorded and tabulated for each run. The axial shortening was determined by measuring the length of the samples before and after the welding procedure. All length measurements were performed using a Vernier caliper. Tensile testing was accomplished using a universal tensile testing machine according to ASTM D638-14 [24]. Figure 2 shows the dimensions of the tensile test specimen. All tensile tests were carried out at a 5 mm/min rate. The ultimate TS reading for each sample was used in the RSM analysis. All statistics were performed using Minitab® 19 with a confidence level of 95%.
Tensile test specimen dimensions
All welding runs were completed within one session to minimize any variation that could arise if the samples were welded in patches. The welding order was followed according to the randomized order outcome from the statistical software. Figure 3 shows welded samples at various process conditions resulting in different flash formations.
HDPE rods joined using CDFW according to different welding conditions. CDFW, continuous drive friction welding; HDPE, high-density polyethylene
Data normality check using the normal probability plot, the versus fits, the histogram, and the versus order for
Analysis of variance
Source | DF | Adj SS | Adj MS | F-Value | P-Value |
---|---|---|---|---|---|
Model | 17 | 7297.99 | 429.29 | 50.12 | 0.000 |
Linear | 6 | 7162.50 | 1193.75 | 139.37 | 0.000 |
1 | 1510.42 | 1510.42 | 176.34 | 0.000 | |
1 | 467.61 | 467.61 | 54.59 | 0.000 | |
RS | 4 | 5184.47 | 1296.12 | 151.32 | 0.000 |
Square | 2 | 92.92 | 46.46 | 5.42 | 0.008 |
|
1 | 40.66 | 40.66 | 4.75 | 0.034 |
|
1 | 63.98 | 63.98 | 7.47 | 0.009 |
2-Way Interaction | 9 | 42.58 | 4.73 | 0.55 | 0.828 |
1 | 18.43 | 18.43 | 2.15 | 0.149 | |
4 | 20.98 | 5.24 | 0.61 | 0.656 | |
4 | 3.17 | 0.79 | 0.09 | 0.984 | |
Error | 47 | 402.56 | 8.57 | ||
Lack-of-Fit | 27 | 287.51 | 10.65 | 1.85 | 0.080 |
Pure Error | 20 | 115.06 | 5.75 | ||
Total | 64 | 7700.56 |
Table 4 shows the regression equations for each of the five RS's. It can be noted that the value of the constant-coefficient increases as the RS increases. The linear terms’ coefficients are much more significant than the square terms’ coefficients or the two-way interactions between the factors. The surface and contour plots are used for visualizing and understanding the process parameters’ effects. Figure 5 shows the surface and contour plots of the welding process parameters according to the RS.
Regression equation in coded parameters
082 |
|
165 |
|
300 |
|
400 |
|
550 |
|
3D surface and contour plots for the maximum welding temperature. The maximum reported values are actual measured values for each speed level
It can be seen that
As RS increases from 82 rpm to 550 rpm, the noticeable differences in the
The axial shortening was analyzed in the statistical design as a second response. Figure 6 shows the plots of the design used to check for data normality. It is evident that the assumption of the data being normal is valid; hence, the validity of the statistical analysis and regression model is satisfied. Most of the data are located on a straight line in the normal probability plot. There is no evident order of the data in the versus fits and versus order plots. Finally, the histogram plots’ data distribution resembles a “bell-shaped” curve that supports the data's normality assumption.
Data normality check using the normal probability plot, the versus fits, the histogram, and the versus order for the axial shortening
Table 5 shows the results of the ANOVA for the axial shortening. The statistical analysis in Table 5 shows that friction time is the most statistically significant parameter affecting the axial shortening of CDFW of HDPE rods. The
Analysis of variance for the axial shortening
Model | 17 | 492.737 | 28.9845 | 174.17 | 0.000 |
Linear | 6 | 445.319 | 74.2199 | 446.00 | 0.000 |
1 | 97.663 | 97.6626 | 586.87 | 0.000 | |
1 | 30.961 | 30.9606 | 186.05 | 0.000 | |
4 | 316.696 | 79.1740 | 475.77 | 0.000 | |
Square | 2 | 1.404 | 0.7021 | 4.22 | 0.021 |
|
1 | 0.006 | 0.0058 | 0.03 | 0.853 |
|
1 | 1.352 | 1.3516 | 8.12 | 0.006 |
2-Way Interaction | 9 | 46.014 | 5.1126 | 30.72 | 0.000 |
1 | 3.486 | 3.4861 | 20.95 | 0.000 | |
4 | 37.344 | 9.3360 | 56.10 | 0.000 | |
4 | 5.184 | 1.2959 | 7.79 | 0.000 | |
Error | 47 | 7.821 | 0.1664 | ||
Lack-of-Fit | 27 | 5.567 | 0.2062 | 1.83 | 0.084 |
Pure Error | 20 | 2.254 | 0.1127 | ||
Total | 64 | 500.559 |
The square terms in the ANOVA table representing the continuous parameters’ square levels indicate that
Regression equation in coded parameters for the axial shortening
082 |
|
165 |
|
300 |
|
400 |
|
550 |
|
Figure 7 shows the surface and contour plots for the axial shortening for all levels of RS. At 82 rpm, there seems to be a “saddle” region in the surface plots, and the axial shortening never exceeds 2 mm. Minimum axial shortening occurs at very large or very small values of
3D surface and contour plots for the axial shortening according to RS's. The maximum reported values are actual measured values for each speed level
The joints’ TS was evaluated as the third and final response in the experimental design. As mentioned in the methodology section, the TS data collected were tabulated and analyzed. Figure 8 shows the validity of the assumptions required for the RSM analysis. All plots within the figure indicate that the assumption of normal data distribution is satisfied, thus demonstrating the validity of the analysis. The factors’ effects and corresponding levels on the Pareto chart are illustrated in Figure 9. Since the chart displays the effects’ absolute value, one cannot predict the factors’ effects. Instead, it indicates the relatively large effects caused by the factors. The figure suggests that the RS has the most considerable effect on TS. The interaction between friction and RS has the second-largest effect, and the frictional force has the third-largest effect.
Data normality check using the normal probability plot, the versus fits, the histogram, and the versus order for the TS. TS, tensile strength
Pareto chart of the standardized effects for the TS of the joints. TS, tensile strength
The ANOVA results of the analysis are indicated in Table 7. The results show the significance of the model that predicts the TS (
ANOVA for TS
Model | 17 | 243.893 | 14.347 | 4.34 | 0.000 |
Linear | 6 | 163.399 | 27.233 | 8.25 | 0.000 |
1 | 4.031 | 4.031 | 1.22 | 0.275 | |
1 | 17.543 | 17.543 | 5.31 | 0.026 | |
4 | 141.825 | 35.456 | 10.74 | 0.000 | |
Square | 2 | 8.616 | 4.308 | 1.30 | 0.281 |
|
1 | 4.475 | 4.475 | 1.36 | 0.250 |
|
1 | 5.260 | 5.260 | 1.59 | 0.213 |
2-Way Interaction | 9 | 71.878 | 7.986 | 2.42 | 0.024 |
1 | 2.833 | 2.833 | 0.86 | 0.359 | |
4 | 42.229 | 10.557 | 3.20 | 0.021 | |
4 | 26.816 | 6.704 | 2.03 | 0.105 | |
Error | 47 | 155.205 | 3.302 | ||
Lack-of-Fit | 27 | 108.605 | 4.022 | 1.73 | 0.106 |
Pure Error | 20 | 46.600 | 2.330 | ||
Total | 64 | 399.098 |
The model also predicts the TS's expected values for all process parameters, as indicated in Table 8. The constant-coefficient suggests that the TS is expected to be very low at 82 rpm, followed by 550 rpm and 300 rpm. On the other hand, the RS's of 165 rpm and 400 rpm seem to allow the TS to reach its maximum potential value. The coefficients of the square and two-way interaction terms agree with the ANOVA results, suggesting that these terms’ effects on predicting the TS are not as prominent as the linear terms.
Regression equations for predicting the TS
082 |
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165 |
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300 |
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400 |
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550 |
|
Figure 10 shows the surface and contour plots for the TS as a function of all process parameters being studied. At 82 rpm, the maximum predicted TS is about 12 MPa, which can be achieved by choosing
Surface and contour plots of the TS as a function of
The maximum welding temperature depends mainly on the friction time and the RS since these two parameters had the highest
The heat generation at any moment during the CDFW process is governed by Eq. (1) as given by Can
The RSM analysis for the axial shortening indicated that all process parameters significantly affect the response outcome. In addition, the interaction between RS and
A different situation was observed to prevail in the case of the tensile strength response. For
The maximum TS achieved was 14.9 MPa, about 66% of the TS of unwelded HDPE. The maximum TS is relatively close to that in other studies [13,14,15,16, 19]. The joints of HDPE made by CDFW seem to have the best TS for an RS level of 300 rpm. The median value of RS being the most suitable indicates a balance in the material consumption within this speed and the heat generated that led to the highest joint efficiency. Being a rotational process that depends on radial distance, the rods’ central parts requiring welding are the most difficult to weld [26].
Moreover, the maximum TS was achieved by either very high speed and low friction time or very low speed and very high friction time. This indicates that the material within these settings becomes suitable for forming strong bonds and, thus, strong joints. As it happens, the axial shortening is affected in the same way the least axial shortening was observed in these conditions. Usually, the outer regions are welded, and the central part remains unwelded. At 300 rpm with various levels of process parameters, the results are inductive that a considerable portion of the contact surfaces is welded. Figure 11 compares the shapes of the welded joints corresponding to various process conditions. The images were arranged from top left to bottom right according to axial shortening from 0.15 mm to 12.8 mm at approximately 1 mm intervals.
Effect of process parameters on the appearance of welded joints arranged according to axial shortening from minimum to maximum
The current study investigated joining rods made of HDPE material using CDFW. Experimental design through RSM analysis was used to statistically explore the ranges of process parameters and responses of interest. Through 65 experiments, the evaluation and prediction of the effects of the process parameters on The RS and friction time affect the maximum welding temperature and axial shortening more than the friction force. The TS depends on the RS and friction force since the friction time was statistically insignificant. An RS of 300 rpm was the most appropriate rotating speed for achieving the desired outcomes. TS of >65% of the material's TS was acquired for a vast range of process parameters. The welding temperature was high enough to form a good joint without reaching the material's melting point. Minimum axial shortening was also achieved, which is a desirable outcome since material losses would be minimal while maintaining strength.
Future work can achieve higher percentages of joint TS without compromising axial shortening and considering the interface's maximum welding temperature.