Roughness optimization of flow-formed tubes using the Taguchi method

Int J Adv Manuf Technol (2014) 72:1009–1019 DOI 10.1007/s00170-014-5732-8

ORIGINAL ARTICLE

Roughness optimization of flow-formed tubes using the Taguchi method Amin Abedini & Samrand Rash Ahmadi & Ali Doniavi

Received: 27 July 2013 / Accepted: 16 February 2014 / Published online: 7 March 2014 # Springer-Verlag London 2014

Abstract The present study reports the effect of various flowforming process parameters and roller geometry on the roughness of flow-formed tubes of commercial pure copper UNS C11000. Thickness reduction ratio, feed rate, angular speed of mandrel, attack angle of roller, roller tip radius, and smooth angle of roller were considered as variable parameters. The effects of these input parameters on the roughness have been critically analyzed using the Taguchi method. Through ANOVA analysis, it has been found that the roller tip radius is the most important parameter affecting roughness followed by thickness reduction ratio. Selection of an optimum combination of variable parameters was performed based on “average of results.” The minimum roughness of 1.37 μm was achieved when the process parameters were set at their optimum values. Keywords Flow forming . Roller geometry . Roughness . Taguchi method

1 Introduction Flow forming, which is also known as tube spinning, is an advanced, chipless, and cost-effective metal forming process to produce precise, seamless, and axisymmetric tubular products [1] although, recently, some methods of nonaxisymmetrical flow forming have been presented [2]. Flowformed parts are widely used in aeronautics, vehicle industry, weaponry, and many other fields of industry. Flow forming A. Abedini : S. Rash Ahmadi (*) : A. Doniavi Mechanical Engineering Department, Urmia University, Urmia, Iran e-mail: [email protected] A. Abedini e-mail: [email protected] A. Doniavi e-mail: [email protected]

applies a simple incremental rotary mechanism to form parts. In this process, a pre-form is fitted to a mandrel and then an angular speed is given to the mandrel. A compression force is applied to the outer diameter of the pre-form by a set of rollers (one or more rollers); this set of rollers is moved along the mandrel axis to reduce the thickness of the pre-form. The metal is displaced axially along the mandrel, while the internal diameter remains constant. Because of conservation of volume, the length of the part increases as its thickness decreases. Axial movement of rollers is called feed rate. There are two types of flow forming, backward and forward flow forming [3]. This categorization is based on the direction of axial flow of the material during the process. In forward flow forming as shown in Fig. 1, the material flows in the direction of the movement of rollers; in other words, the direction of feed rate and the material flow are the same. Forward flow forming is used when the pre-form has one closed or semi-closed end. In backward flow forming as shown in Fig. 2, the material flows in the opposite direction of the movement of rollers. Backward flow forming is used when the pre-form has two open ends, such as tubes. Flow forming has many advantages such as improvement in mechanical properties due to cold work, sound finished surface, high dimensional accuracy, simple tool design, low cost, high productivity, etc. [4]. These advantages have made flow forming a very attractive process for both the academia and industry [5]. Many experimental, numerical, and analytical researches have been carried out in the field of flow forming. Davidson et al. experimentally studied some parameters of the flow-forming process that affect the surface quality of the flow-formed AA6061 aluminum alloy tubes [6]. Hua et al. established a 3D elastic-plastic finite element model for flow forming and studied the deformation and stress-strain distribution [7]. Zhan et al. performed a 3D finite element model to study the effect of process

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Fig. 1 Forward flow forming

parameters on the forming force and quality of formed parts in the cone spinning process [8]. Roy et al. established an analytical solution to predict the shape of the interface of the roller/work piece. They claimed their model can predict the shape of the contact zone and this can be applied in all branches of metal spinning [9]. Ekinovic et al. performed an experimental study to investigate the effect of cold flow forming on the cutting force of next machining on the flow-formed part. They studied the changes between cutting force due to cold forming of the pre-form [10]. Haghshenas et al. appraised the local true plastic strain during flow forming of AISI1020 steel pre-form, and they investigated the von Mises equivalent true plastic strain due to different thickness reduction ratios [11]. Podder et al. studied the effect of heat treatment of pre-form on the mechanical properties and formability of AISI4340 steel [12]. Flow forming has a very complicated tool-work piece interaction and there are numbers of parameters that affect the finished part quality. Surface quality called roughness is an important feature of a part. Roller geometry has a very crucial role in the flow-forming process. As shown in Fig. 3, roller geometry directly affects the shape of the contact-forming zone of the work piece and has important consequences on the roughness of the formed parts. But no work has been reported considering roller geometry and its interaction with other parameters of the flow-forming process. As it is mentioned before, roughness is an important feature of a part, and during flow forming, the roller directly affects the surface quality of the part. This study was performed to investigate and optimize the effects of

Fig. 2 Backward flow forming

Fig. 3 Effect of roller geometry on the shape of the contact zone

roller geometry and other process parameters on roughness using the Taguchi method. The details of roller geometry were shown in Fig. 4.

2 Experimental work 2.1 Flow forming Flow forming is an advanced, rapid, cold, and hot work process (in some cases like CNG or oxygen capsules, flow forming is implemented at an elevated temperature) to produce seamless, dimensionally precise tubular parts. Because of using an incremental and localized deformation area, flow forming needs comparatively lower forming forces. 2.2 Roughness Surface roughness, often called roughness, is a measure to evaluate the texture of a surface. It is quantified by the vertical deviations of a real surface from its ideal form. If these deviations are large, the surface is rough; if they are small, the surface is smooth. Roughness is typically considered to be the high frequency, short wavelength component of a measured surface. Roughness plays an important role in determining how a real object will interact with its environment. Rough surfaces usually wear more quickly and have higher friction coefficients than smooth surfaces. Roughness is often a good predictor of the performance of a

Fig. 4 Details of roller geometry

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Fig. 5 Representation of averaged depth of roughness parameter (Ra) definition according to DIN 4768

Fig. 8 Pre-form dimensions, millimeters

Fig. 6 Flow-forming machine

mechanical component, since irregularities in the surface may form nucleation sites for cracks or corrosion. Although roughness is usually undesirable, it is difficult and expensive to control during manufacturing processes. Decreasing the roughness of a surface will usually increase exponentially its manufacturing costs. This often results in a trade-off between the manufacturing cost of a component and its performance in practice. There are many different roughness parameters in use, but Ra is by far the most common. Other common parameters

Fig. 9 Annealing furnace

Table 1 Nominal composition of copper UNS C11000

Element

Cu

O

Fe

wt%

99.9

0.04

0.02

Table 2 Mechanical properties of copper UNS C11000

Fig. 7 Digital roughness tester

Feature

Density (g/cm3)

Poisson’s ratio

Elastic modulus (GPa)

Tensile strength (MPa)

Value

8.8–8.94

0.34

117

210

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Fig. 10 Steps of application of the Taguchi method

START Identification of the response functions and the process parameters Determination of the number of levels for the process parameters Selection of the appropriate orthogonal array Carrying out the trials and measuring the value of response function Selection of the optimum level of process parameters through ANOVA analysis

Is the combination of optimal levels one of the trials of selected orthogonal array?

No

Performing a confirmation

Yes

experiment to verify the optimal

Reporting the combination and measured value as optimal END

include Rz, Rq, and Rsk. Some parameters are used only in certain industries or within certain countries. Each of the roughness parameters is calculated using a formula for describing the surface. In this study, Ra was considered as roughness indicator. The arithmetic mean roughness parameter (Ra) specifies the arithmetic mean of the absolute amounts of all variances in the roughness profile from the center line over the total distance as Eq. 1 [13]:

Fig. 11 Changeable design of roller

l

Ra ¼

1 ∫ j f ðxÞjdx l 0

ð1Þ

Table 3 Process parameters and levels Parameter

Low

Medium

High

Thickness reduction (%) Feed rate (mm/rev) Angular speed (rpm) Attack angle (deg) Tip radius (mm) Smooth angle (deg)

20 0.1 63 10 2 2

40 0.51 180 20 3 4

60 1.01 355 30 4 6 Fig. 12 Different rollers based on L27 orthogonal array

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Fig. 13 Pre-forms and flowformed tube

where l is the total sampling length and f(x) is the surface profile height to the center line average (m), and it is a function

Table 4 L27 array and measured roughness

of position. Ra is expressed in units of height. A schematic representation of Ra was expressed in Fig. 5.

Run

Thickness reduction ratio

Feed

Angular speed

Attack angle

Tip radius

Smooth angle

Roughness (μm)

1 2 3

L L L

L L L

L L L

L L L

L M H

L M H

5.0 4.0 7.0

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

L L L L L L M M M M M M M M M H H H

M M M H H H L L L M M M H H H L L L

M M M H H H M M M H H H L L L H H H

M M M H H H H H H L L L M M M M M M

L M H L M H L M H L M H L M H L M H

L M H L M H M H L M H L M H L H L M

2.5 2.5 5 4.5 5.0 5.6 3.0 3.0 6.0 2.0 3.5 5.0 5.0 5.5 7.0 3.5 5.0 6.4

22 23 24 25 26 27

H H H H H H

M M M H H H

L L L M M M

H H H L L L

L M H L M H

H L M H L M

5.0 6.6 7.0 6.5 8.0 8.7

Int J Adv Manuf Technol (2014) 72:1009–1019 10 9 8 7 6 5 4 3 2 1 0

7 6

Roughness

Roughness

1014

5 4 3 2 1

1

3

5

7

9

11 13 15 17 19 21 23 25 27

0

Trail number

L

M

H

level

Fig. 14 Plotted points of measured roughness of trials

Fig. 16 Effect of different levels of thickness reduction ratio on roughness

2.3 Equipment 2.3.1 Flow-forming machine

2.3.2 Roughness tester

This study was implemented on a single roller flow-forming machine. The machine was an NC lathe and a set of rollers and mandrel was designed and manufactured to convert the lathe to a flow-forming machine. The lathe machine has identical principals of movement as flow-forming machines have. The roller was made from SPK steel with a high measure of precision. The roughness of the rollers was 1 μm. Figure 6 shows the flow-forming machine. Angular speed was applied in rotation per minute (rpm), feed rate was applied in millimeters per revolution, and the amount of thickness reduction was applied as a dimensionless ratio that is represented by Eq. 2 and called as thickness reduction ratio [7], where t0 is the initial wall thickness of the pre-form and tf is the wall thickness of the flow-formed part.

A digital roughness tester shown in Fig. 7 was used in this study to calculate the roughness of the parts.

t 0 −t f Thickness reduction ratio ¼  100 t0

ð2Þ

Fig. 15 Probability plot of the measured roughness data

2.4 Pre-form design Figure 8 shows the pre-form design and its dimensions used in this study. This pre-form was manufactured by the extrusion technique in the form of a long pipe. A saw machine was used to cut this long pipe to its desired length. After milling the lug, pre-forms were annealed at 200 °C for 2 h and cooled in air to eliminate the effects of previous cold works. Figure 9 shows the furnace at annealing temperature. 2.5 Roller geometry Figure 4 shows the roller geometry. In this study, the attack angle, tip radius, and smooth angle were considered as geometrical variables.

Probability Plot of roughness Normal - 95% CI 99

Mean StDev N AD P-Value

95

Percent

90 80 70 60 50 40 30 20 10 5 1

0

2

4

6 roughness

8

10

5.104 1.732 27 0.344 0.461

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2.6 Material The material used in this study was commercial pure copper UNS C11000, which is normally soft and ductile and contains less than 0.7 % of total impurities. The chemical composition and mechanical properties of UNS C11000 were shown in Tables 1 and 2, respectively.

3 Design of the experiment This study was implemented on the basis of the Taguchi method, which is a simple, powerful, and cost-effective design of experimental tools. The Taguchi method has a systematic approach to determine optimal process parameters. The conventional methods of experiment design are too complex and expensive. These conventional methods need a large number of experiments to be carried out and also too much money and time. Moreover, traditional methods involve one-factor-at-a-time experiments in which one variable is changed while the rest are held constant. The major disadvantage of these methods is the failure to consider any possible interactions between the parameters. The Taguchi method offers an orthogonal array to study the entire process with only a small number of experiments. Using this orthogonal array, the Taguchi technique overcomes all the deficiencies of traditional methods. The Taguchi method is used for optimizing process parameters and identifying the optimal combination of factors for the desired responses [5]. The steps involved are as shown in Fig. 10 [14]. The input parameters chosen for this study, as shown in Table 3, were thickness reduction ratio, feed rate, angular speed of mandrel, and roller geometry, which includes the attack angle, tip radius, and smooth angle. These parameters were considered at three levels: low, medium, and high. The response function was surface Fig. 17 Fish scale marks due to low thickness reduction ratio

Fig. 18 Nonuniform deformation due to high thickness reduction ratio

roughness. Table 3 shows the parameters and their levels. An L27 orthogonal array was used which can handle three-level process parameters. Twenty-seven experiments were required to be carried out in order to shape the 27 different rollers needed. That was the most timeconsuming and tedious part of this study. To reduce the cost of materials, a changeable setting for the rollers was designed that needed changing only the roller ring, but the axle and housing did not need any changes. Figure 11 shows the exploded parts of the axle of the roller and its assembled setting. Figure 12 shows the 27 different rollers made for this study. If a conventional design of the experiment was considered, numerous numbers (36 =729) of trials would be implemented that is totally impossible or timeconsuming. Figure 13 shows the pre-forms of this study and a flow-formed part. Table 4 shows the layout of this study and measured roughness for runs. The capital letters L, M, and H indicate low level, medium level, and high level, respectively.

4 Results and analysis The experimental results were analyzed, to recognize the main effects of process parameters on the surface quality of the

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Roughness

1016 7 6 5 4 3 2 1 0

L

M

H

level Fig. 19 Effect of different levels of feed rate on roughness

flow-formed parts. The overall average of roughness was 5.1 μm that is an excellent surface quality. This capability makes flow forming a desired process to produce sound and precise parts. Figure 14 shows the plotted point of measured roughness of trials. According to this diagram, trial number 27 has the roughest surface and trial number 13 had the smoothest surface. Figure 15 shows the probability plot of the measured roughness data. The probability plot for the roughness data shows that the data points for this distribution fall close to the fitted normal line and within the confidence interval. Furthermore, the p value (0.461) is above any reasonable significant level. These facts suggest that the normal distribution fits the roughness data well. Because the distribution fits the data, it is readily possible to use the fitted line to estimate percentiles for the population. 4.1 Main effects 4.1.1 Thickness reduction ratio Figure 16 shows the mean roughness at each level of the thickness reduction ratio. This diagram indicates that the medium level of thickness reduction ratio gives better surface quality. At low level of thickness

Fig. 20 Wave-like projection due to high feed rate

reduction, the metal tends to grow in a diametrical direction because of too much cold work on a thin layer of material that increases the roughness of the surface. On the other hand, as shown in Fig. 17, too much cold work results in a high level of strain hardening and causes fish scale marks on the surface and increases roughness. At high level of thickness reduction as shown in Fig. 18 because of a too large contact-forming zone, friction increases, and consequently, the forming force increases, and this causes vibration in the system. Vibration affects the uniformity of metal displacement and increases surface roughness. 4.1.2 Feed rate Figure 19 shows the mean roughness at each level of feed rate. The medium level of feed rate gives better surface quality. The low level of feed rate results in an increase in surface roughness. It seems that the plastic deformation is delayed by the lower feed rate, and instead of flowing in the axial direction, it flows in the radial direction resulting in diametrical growth and poor surface quality. The high level of feed rate makes the roller move faster through the mandrel that denies the plastic deformation as shown in Fig. 20 making wave-like projections on the surface that worsens the surface quality. 4.1.3 Angular speed Figure 21 shows the mean roughness at each level of angular speed. A high level of angular speed gives a better surface quality. The diagram shows a higher angular speed and a better surface quality. But a very high angular speed must be avoided because of vibration problems. Bed and damping system of each machine can absorb a restricted amount of vibration, so in angular speed determination, these limitations must be considered.

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7

7

6

6

5

5

Roughness

Roughness

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4 3 2

4 3 2 1

1

0

0

L

M

L

H

M

H

level

level Fig. 21 Effect of different levels of angular speed on roughness

Fig. 23 Effect of different levels of tip radius on roughness

4.1.4 Attack angle

applies high cold work to the area and causes difference in mechanical properties between the superficial layer and the inner layer. These differences make various amounts of spring-back in the inner and outer layers that affect surface uniformity and result in high roughness.

Figure 22 shows the mean roughness at each level of the attack angle. A low level of attack angle results in high roughness. This is because of too much cold work that is applied on the material. If a lower attack angle is chosen, the plastic deformation is initiated too early. Until the tip of the roller touches the material, it bears too much cold work that makes the material harder due to strain hardening. A high level of attack angle results in a sudden initialization of a thick layer plastic deformation that produced vibration in the machine. As mentioned above, vibration is an unwanted factor during flow forming, because it worsens the surface quality. 4.1.5 Tip radius Figure 23 shows the mean roughness at each level of the tip radius. A low level of tip radius gives better surface quality; this is because of a smaller contact-forming zone relative to a small roller tip radius. A small contact-forming zone needs lower forming forces that reduce vibration in the system. On the other hand, a very small tip radius should be avoided because a too small tip radius applies forming force on a small area, so stress in the forming zone reaches the ultimate stress and causes fracture and makes fish scale-like marks on the surface. A large tip radius expands a contact-forming zone and

4.1.6 Smooth angle Figure 24 shows the mean roughness at each level of the smooth angle. A low level of smooth angle results in a rough finished surface. This is because of expanding the contact zone due to a small release angle of material right after the tip radius. In this contact zone, the material is relaxed from yield stress and has its solid shape, so the roller slides on the surface and destroys the surface quality of the flow-formed tube. A high level of smooth angle causes premature relaxation of stress that resulted in dimensional inaccuracy that worsened the surface quality in comparison with the medium level of the smooth angle. 4.2 Analysis of variance (ANOVA) The results of ANOVA for roughness as response function are given in Table 5. Comparison of the percentage contributions of the parameters indicated that the roller tip

5.6

5.6 5.4

5.2

Roughness

Roughness

5.4 5 4.8 4.6

5 4.8 4.6

4.4 4.2

5.2

L

M

H

level Fig. 22 Effect of different levels of attack angle on roughness

4.4

L

M

H

level Fig. 24 Effect of different levels of smooth angle on roughness

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Table 5 ANOVA results Factor

Degree of freedom

Sum of squares

Mean of squares

F0

Percentage

Rank

Tip radius Thickness reduction ratio Feed rate Angular speed Attack angle Smooth angle Error Total

2 2 2 2 2 2 14 26

25.14 19.39 17.30 7.57 2.97 2.30 3.36 78.03

12.57 9.69 8.51 3.78 1.48 1.15

5.7 3.97 3.35 1.29 0.47 0.36

32.22 24.85 21.82 9.70 3.81 2.94

1 2 3 4 5 6

Table 6 Optimum levels for the process parameters Factor

Thickness reduction ratio

Feed rate

Angular speed

Attack angle

Tip radius

Smooth angle

Level Value

Medium 40 %

Medium 0.51 mm/rev

High 355 rpm

Medium 20°

Low 2 mm

Medium 4°

radius was the most significant parameter that influenced the surface quality. After the tip radius, the parameter which has the second most significant effect was thickness reduction ratio followed by feed rate. Angular speed achieved the fourth rank, while attack angle and smooth angle did not have a significant percentage of contribution and were ranked fifth and sixth, respectively. 4.3 Optimum levels and confirmation run Table 6 shows the optimum conditions to attain high surface quality. Based on the “average of results” to achieve the lowest roughness, thickness reduction ratio should be at medium level, feed rate should be at medium level, angular speed should be at high level, attack angle should be at medium level, tip radius should be at low level, and smooth angle should be at medium level. This model predicted an optimum value of 1.44 μm for roughness. Since the optimum combination was not in the experimental runs of the experiment layout (L27 orthogonal array), an extra confirmation run was required. The confirmation run was carried out at optimum levels and the value of 1.37 μm for roughness was measured and it was significantly close to roughness of the rollers. The predicted value and practical value for roughness of confirmation test were highly close.

5 Conclusion The process parameters that affect the flow-forming process have been studied using the Taguchi technique. The variables affecting roughness according to their relative significance are

roller tip radius, thickness reduction ratio, feed rate, angular speed of mandrel, attack angle, and smooth angle, respectively. The optimum process levels indicated that in order to attain high surface quality, the variables must be as follows: thickness reduction ratio=40 %, feed rate=0.51 mm/rev, angular speed=355 rpm, attack angle=20°, tip radius=2 mm, and smooth angle=4°. The confirmation run showed that setting of process parameters at their optimum levels can ensure significant improvement in roughness. The optimized roughness value of 1.37 μm was achieved. The optimized value of roughness was too close to the roughness of the rollers.

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