Effect of evaporative pattern casting process parameters on the surface roughness of Al–7% Si alloy castings

Journal of Materials Processing Technology 182 (2007) 615–623

Effect of evaporative pattern casting process parameters on the surface roughness of Al–7% Si alloy castings Sudhir Kumar ∗ , Pradeep Kumar, H.S. Shan Mechanical & Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, Uttaranchal, India Received 14 December 2005; received in revised form 16 August 2006; accepted 11 September 2006

Abstract Evaporative pattern casting (EPC) process has drawn great attention from both academia and industry in recent years. The expandable polystyrene (EPS) pattern is a key feature of EPC process which is buried in unbonded sand and replaced by molten metal. This paper investigates the effect of process parameters like degree of vacuum, pouring temperature, grainfiness number, amplitude of vibration and time of vibration on the surface roughness of Al–7% Si alloy castings in EPC process. In order to evaluate the effect of selected process parameters, the response surface methodology (RSM) is used to formulate a mathematical model which correlates the independent process parameters with the desired surface roughness. The central composite rotatable design has been used to conduct the experiments. The analysis of results indicates that the surface roughness increases with increase in degree of vacuum, pouring temperature. Whereas, it has an inverse relationship with grainfiness number, amplitude of vibration and time of vibration. © 2006 Published by Elsevier B.V. Keywords: EPC process; Process parameters; Surface roughness; Response surface methodology (RSM)

1. Introduction Evaporative pattern casting (EPC) process offers several advantages over conventional sand casting processes, such as simplified production techniques, and reduces environmental waste due to binder emissions and sand disposal. The process is well-suited for castings with complex geometries, tight tolerances, and smooth surface finish requirements. When the castings are designed to fully exploit these advantages, cleaning and machining times are dramatically reduced if not completely eliminated. Therefore, the EPC process is viewed as a value-added process rather than a substitute for sand casting. In EPC process, pattern is usually made of expandable polystyrene (EPS). The use of a polystyrene pattern increases dimensional accuracy, and gives improved casting quality, compared to conventional casting [1]. Barron indicates that smooth surface of the pattern can be obtained by use of small, light weight polystyrene beads and thin walled low density pattern [2].

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Corresponding author. Tel.: +91 9412420113. E-mail addresses: s k [email protected], [email protected] (S. Kumar). 0924-0136/$ – see front matter © 2006 Published by Elsevier B.V. doi:10.1016/j.jmatprotec.2006.09.005

In this process, the sand mold contains no binder and moisture and hence the refractoriness of the mold is entirely dependent upon the molding sand [3]. The sand without binder leads to a defective casting due to sand falling problem. An attempt is made to bind the EPC mold by creating vacuum in the mold while mold is sealed from the both end by polyethylene film [4]. Any type of molding sand can be used for the process as long as the sand resists the temperature of the molten metal being poured [3]. Silica sand, zircon sand, olivine sand and chromites can be used as molding sand. Due to high degree of sand reclamination in EPC process, expensive sands such as zircon or chromites can be used [5]. The strength of the mold is determined by frictional resistance between the sand grains. The strength of the mold is higher with angular grains, although rounded grains provide a higher bulk density [6,7]. The density of free flowing sand can be increased by vibration. Leighton Buzzard sand compacted by vibration was found to have a density 12.5% greater than for unvibrated sand or resin bonded sand which had been lightly rammed [8]. Bennett et al. have studied various gating arrangements for the different aluminum castings to determine the pyrolysis defects. Pyrolysis defects with foam sprue were found to be greater compared to untapered hollow ceramic sprue. Multiple gates also had little effect on reducing defects. When the pattern was oriented vertically, top gating was

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observed to increase defects whereas bottom gating completely eliminated the defects [9]. The mechanism of misrun formation in EPC process has been investigated in A356 aluminum castings based on the surface appearance, fill pattern and microstructure of various misruns [10]. Warner et al. suggested the low metal velocity to reduces or eliminate folds, bilsters and internal porosity defects [11]. Effect of various process variables such as area to parameters, metalastic head pressure and the properties of sand, coating on the fluidity of aluminum alloy in EPC process has been studied [12]. In the paper an attempt has been made to evaluate the effect of process parameters on the surface roughness of Al–7% Si alloy castings in the EPC process. In order to evaluate the effect of process parameters on the surface roughness, response surface methodology (RSM) was applied. The RSM was used to correlate the independent process parameters with the surface roughness by a mathematical model. The second order response surface was found sufficient for the present work. The central composite rotatable design was used to plan the experiments. 2. Pattern density and bead size Density and bead size play important role in evaporative pattern casting process. A low density pattern is required to minimize the amount of gas evolved during vaporization of the pattern. Since the gas must permeate through the coating, sand and vent into the atmosphere. If the gas forms faster than it can vent, a defective casting will result. Gas formation is a function of pattern density and metal pour temperature. If pattern density is increased, more gas formed at a constant pour temperature. If pattern density is held constant and pour temperature is increased, more gas formed since the polystyrene molecules will break down into more basic molecules at the higher temperature. Steel castings generally required a lower density pattern than gray, malleable or ductile iron, ferrous castings require a lower density than copper alloys, which in turn need a lower density than aluminum castings. The ratio of surface area to volume must also be considered. All the gas formed must pass through the coating on the surface of the pattern. Pattern density varies between 1.0 and 1.5 pcf depending on the geometry and metal being poured. Regarding bead size, a small bead is required to obtain a relatively non-beady, smooth surface on molded patterns. In addition, a small bead will also enable filling of thin wall section (e.g. 1/4 in. and less) common on many patterns [13]. 3. Requirement of refractory coating material Coatings are integral part of casting production, since they provide a good quality surface of castings without glued and baked sand. With development of casting engineering, a demand for quality coatings is increasing for use of new refractory fillers, suspension agents and binders as well as improving manufacturing technology [14]. Ballmann [15] suggested that the refractory coating for application in evaporative pattern casting process must satisfy a number of specific demands as follows:

• Highly permeable coating is used for rougher sand while medium and low permeable coating is used for finer sand. • Quick drying. • Coating should be easily stuck to the pattern, and there should be possibility of controlling and adjusting coating layer thickness. • Appropriate strength, resistance to abrasion, resistance to cracks during storage, resistance to bending and deformation during mould making. • If rougher sand is used for mould making and a high casting temperature, then the refractory coating layer should be thicker. 4. Selection of coating material There are several kinds of evaporative pattern coating with different thermo-physical characteristic, which are specially designed to meet number of requirements of the evaporative pattern casting process [14]. Dieter [16] used zircon flour coating for aluminum alloy whereas Trumbulovic [14] used kaolin and talc for the coating. Sodium silicate coating is not recommended because they lack permeability and can lead to metal splashing during mold filling. For the cast iron, a coating based on iron powder has been found successful in preventing metal penetration problems [17]. The high pouring temperature ranges of cast iron and steel usually dictate the selection of a silica or mullite type refractory [18]. Kumar et al. [19] performed coating analysis using filler materials siliminite, quartz, and aluminum silicate in combination with zircon flour and binder for considering cost economy. In addition, zircon flour with aluminum silicate was found to be low dielectric constant, high density, high viscosity, and pH value nearer to neutral refractory. 5. Evaporative pattern casting process Experimental set of EPC process is shown in Fig. 1. The evaporative pattern casting process starts with the pre-expansion of beads, usually polystyrene, which contain pentane as blowing agents. After the pre-expanded beads are stabilized, they are blown into mold to form pattern sections. When the beads are in the mold, a steam cycle causes them to fully expand and fuse together; this process is followed by an in-mold cooling cycle. The pattern is made to the exact shape of required components, including all shrinkage and machining allowances. Feeders, running and gating systems made in polystyrene are added at the suitable points [20]. The pattern, coated with suitable refractory wash, is embedded in dry, unbonded sand, which is vibrated to produce a rigid mold. Then the mold is encapsulated between two plastic films and vacuum is applied in the sand mold. Vacuum thus rigidizes the mold and mold hardness greater than 85 is achieved. On pouring, the molten metal replaces the polystyrene pattern, precisely duplicating all of the features of the pattern. Thus, quality (dimensional accuracy, surface roughness) of the pattern is of utmost importance as it has the direct bearing on the quality of the castings. After shake out the casting requires minimal fettling because the expandable pattern requires no mold joint line and cores may be entirely eliminated. The molding

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Fig. 1. Experimental setup of evaporative pattern casting process. 1, Vacuum gauge in main line; 2, main control valve; 3, control valves in sub line for cope and drag; 4, vacuum gauge in sub line; 5, molding box (cope); 6, molding box (drag); 7, vibrator; 8, spring; 9, motor; 10, vacuum pump; 11, water tank; 12, water outlet valve; 13, inlet control valve of vacuum pump; 14, outlet control valve of vacuum pump; 15, surge tank; 16, vari-drive motor control switch; 17, main starting switch; 18, vacuum pump control switch.

sand is entirely reclaimable with cooling and classifying the only treatments required [5]. Procedure of EPC process can be summarized as shown in Fig. 2.

The following process parameters were selected to visualize their effect on the surface roughness of castings of Al–7% Si alloy produced by EPC process:

6. Process parameters of EPC process

1. 2. 3. 4. 5.

In order to identify the process parameters that affect the quality of the castings produced by EPC process, an Ishikawa cause–effect diagram was constructed, as shown in Fig. 3. The Ishikwa cause–effect diagram depicts that the following process parameters may affect the surface roughness of the castings produced by EPC process: 1. Molding sand based variables—type, shape, size and size distribution. 2. Vibration based variables—frequency, amplitude of vibration, time of vibration. 3. Vacuum based variables—degree of vacuum imposed. 4. Pouring material based variables—pouring time and temperature. 5. Pattern based variable—density and size of polystyrene beads. 6. Coating based variables—material slurry, thickness.

Degree of vacuum. Pouring temperature. Grainfiness number. Amplitude of vibration. Vibration time.

The other parameters such as frequency of vibration (23.35 Hz), pouring time (5 s), density (22 kg/m3 ), and size of polystyrene beads (1/4 in.) were kept fixed during the entire investigation. The range of the selected process parameters were decided by conducting the experiments with one variable at a time approach. The process parameters, their designated symbols and range are given in Table 1. The Al–7% Si alloy was poured in the EPC process molds. Through the various types of sand such as silica, zircon, olivine, etc., are available, silica sand is used because of its availability in abundance and cost economy. The size of the sand grains was quantified by AFS grainfiness number. The sand of the required AFS number was prepared from the sorted sand and three screen distributions were

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S. Kumar et al. / Journal of Materials Processing Technology 182 (2007) 615–623 Table 1 Process parameters, symbols and their ranges Process parameters

Degree of vacuum Pouring temperature Grain finess number Amplitude of vibration Time of vibration

Symbol

A (mmHg) B (◦ C) C (AFS) D (␮m) E (s)

Levels 2

−1

0

1

2

200 650 60 400 40

250 675 80 430 55

300 700 100 460 70

350 725 120 490 85

400 750 140 520 100

maintained. The shape of the sand grains was almost sphere with sphericity indexes 0.91 [21]. 7. Response surface methodology Response surface methodology is a collection of mathematical and statistical technique useful for analyzing problems in which several independent variables influence a dependent variable or response, and the goal is to optimize the response [22]. In many experimental conditions, it is possible to represent independent factors in quantitative form as given in Eq. (1). Then these factors can be thought of as having a functional relationship or response as follows: Y = Φ(x1 , x2 , . . . , xk ) ± er

Fig. 2. Procedure of evaporative pattern casting process.

(1)

between the response Y and x1 , x2 , . . ., xk of k quantitative factors. The function Φ is called response surface or response function. The residual er measures the experimental errors. For a given set of independent variables, a characteristic surface is responded. When the mathematical form of Φ is not known, it can be approximated satisfactorily within the experimental region by polynomial. Higher the degree of polynomial better is the correlation but at the same time costs of experimentation become higher. For the present work, RSM has been applied for developing the mathematical models in the form of multiple regression

Fig. 3. Ishikawa cause–effect diagram of EPC process.

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Table 2 Components of central composite second order rotatable design Number of variables, k

Number of factorial points

Number of star points

Number of center points

Total, N

Value of α

3 4 5 6

8 16 16a 32a

6 8 10 12

6 7 6 9

20 31 32 53

1.682 2.000 2.000 2.378

a

Half replication.

equations for the quality characteristic of the sand. In applying the response surface methodology, the dependent variable was viewed as a surface to which a mathematical model is fitted. For the development of regression equations related to various quality characteristic of evaporative pattern casting process, the second order response surface has been assumed as [23]: Y = b0 +

k  i=1

b i xi +

k  i=1

bii xi2 +

k 

bii xi xj + er

(2)

i
This assumed surface Y contains linear, squared and cross product terms of variables xi ’s. In order to estimate the regression coefficients, a number of experimental design techniques are available. Box and Hunter [24] has proposed a scheme, based on central composite rotatable design, which fits the second order response surfaces very accurately.

The factor ‘α’ is the radius of the circle or sphere on which the star points lie. With k ≥ 5 the experimental size is reduced by using half replication of 2k factorial design. With half replication, α become 2(k−1)/4 . Also no replication is needed to find error mean square. The error mean square can be found out by replicating the centre points. The components of central composite second order rotatable design for different number of variables are shown in Table 2. 9. Experimental procedure As suggested by the experimental design, 32 castings of the test pattern shown in Fig. 4 were produced. The Al–7% Si alloy was poured in the EPC molds. The response measured was surface roughness. The surface roughness on the top surface of each step of the pattern was measured by using the Optical profilometer. The experimental values for making molds along with the average values of surface roughness are given in Table 3.

10. Results, analysis and discussion 8. Central composite second order rotatable design In this design, standard error remains same at all the points which are equidistant from the centre of the region. This criterion of rotatability can be explained as follows. Let the point (0, 0, . . ., 0) represent the centre of the region in which the relation between Y and x is under investigation. From the result of any experiments, the standard errors, er of Y can be computed at any point on the fitted surface. The standard error acts as a function of the co-ordinates xi ’s of the point. Because of rotatability condition, the standard error is same at all equidistant point with the distance ρ from the centre of region, i.e. for all points for which the following equation holds [25]. x12 + x22 + · · · + xk2 = ρ2 = constant

(3)

Central composite rotatable design is subdivided into three parts: • Points related to 2k design, where k is the number of parameters and 2 is the number of levels at which the parameters is kept during experimentation. • Extra points called star points positioned on the co-ordinate axis to form a central composite design with a star arm of size ‘α’. • Few more points are added at the centre to give roughly equal precision for response Y with a circle of radius unity.

The results of the second order response surface model fitting in the form of analysis of variable (ANOVA) after deleting the insignificant terms are given in Table 4. The determination coefficient (R2 ) indicates the goodness of fit for the model. In this case, the value of the determination coefficient (R2 = 0.86) indicates that only 14% of the total variations are not explained by the model. The value of the adjusted determination coefficient (adjusted R2 = 0.78) is also high, which indicates a high significance of the model [22]. Predicted R2 is a reasonable agreement with the adjusted R2 . Adequate precision compares the range of the predicted values at the design points to the average prediction error. Ratios greater than 4 indicate adequate model discrimination. At the same time a relatively lower value of the coefficient of variation (CV = 8.41) indicates improved precision and reliability of the conducted experiments. After eliminating the non-significant terms, the response surface equation for surface roughness is given as follows: SR = −63.57 + 0.084A + 0.14B + 0.047C + 0.0013D + 0.048E + 0.000046A2 + 0.00016D2 − 0.0001AB − 0.00017AC − 0.00018AE − 0.00022BD

(4)

The value of probability >F in Table 4 for model is less than 0.05 which indicates that the model is significant. In the same way, degree of vacuum (A), pouring temperature (B), grainfiness number (C), amplitude of vibration (D), time of vibration (E), interaction effect of degree of vacuum with pouring temperature

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Fig. 4. (a) Expandable polystyrene pattern and (b) casting of pattern of Al–7% Si alloy.

Table 3 Experimental design, average surface roughness values Standard

Run order

Degree of vacuum

Pouring temperature

AFS number

Amplitude of vibration

Time of vibration

Surface roughness (␮m)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

17 32 5 19 12 15 26 13 1 14 10 29 7 22 23 11 27 25 8 20 4 18 6 31 30 2 28 16 3 21 24 9

250 350 250 350 250 350 250 350 250 350 250 350 250 350 250 350 200 400 300 300 300 300 300 300 300 300 300 300 300 300 300 300

675 675 725 725 675 675 725 725 675 675 725 725 675 675 725 725 700 700 650 750 700 700 700 700 700 700 700 700 700 700 700 700

80 80 80 80 120 120 120 120 80 80 80 80 120 120 120 120 100 100 100 100 60 140 100 100 100 100 100 100 100 100 100 100

430 430 430 430 430 430 430 430 490 490 490 490 490 490 490 490 460 460 460 460 460 460 400 520 460 460 460 460 460 460 460 460

85 55 55 85 55 85 85 55 55 85 85 55 85 55 55 85 70 70 70 70 70 70 70 70 40 100 70 70 70 70 70 70

2.23 3.45 2.89 3 2.02 2.38 3.2 3.2 2.22 3 2.25 2.95 2.14 2.3 2.25 1.75 2.22 3.10 2.1 2.54 2.35 2.45 3.13 2.42 2.5 1.85 2.33 2.3 2.032 2.31 2.32 1.92256

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Table 4 Value of coded and real coefficient with F ratio after deleting insignificant terms (surface roughness) Source

Coded value

Real value

SS

DF

MS

F-Value

Probability >F

Model A B C D E A2 D2 AB AC AE BD

+2.28 +0.19 +0.11 −0.11 −0.21 −0.11 +0.12 +0.14 −0.14 −0.17 −0.14 −0.17

−63.57332 +0.083741 +0.13988 +0.047000 +1.26176E−003 +0.047944 +4.62726E−005 +1.60479E−004 −1.10500E−004 −1.74375E−004 −1.84167E−004 −2.22500E−004

5.24 0.88 0.29 0.27 1.01 0.29 0.40 0.62 0.31 0.49 0.31 0.45

11 1 1 1 1 1 1 1 1 1 1 1

0.48 0.88 0.29 0.27 1.01 0.29 0.40 0.62 0.31 0.49 0.31 0.45

11.02 20.30 6.66 6.26 23.42 6.66 9.24 14.41 7.06 11.25 7.06 10.30

<0.0001 0.0002 0.0178 0.0211 <0.0001 0.0178 0.0065 0.0011 0.0151 0.0032 0.0151 0.0044

0.86 0.71 0.16 6.11

20 15 5 31

0.043 0.047 0.032

1.49

0.3500

R-squared Adjusted R-squared Predicted R-squared Adequate precision

0.8583 0.7804 0.6020 11.971

Residual Lack-of-fit Pure error Cor. total Standard deviation Mean CV Press

0.21 2.47 8.41 2.43

(AB), interaction effect of degree of vacuum with grainfiness number (AC), interaction effect of degree of vacuum with time of vibration (AE), interaction effect of pouring temperature with amplitude of vibration (BD), and second order term of degree of vacuum (A), amplitude of vibration (D) have significant effect. Rest of terms are said to be insignificant. The lack-of-fit term is non-significant as it is desired. The normal probability plot of the residuals for surface roughness is shown in Fig. 5. Fig. 5 revealed that the residuals are falling on the straight line, which means that errors are distributed normally. In Table 5 each of the observed values is compared with the predicted values from the model. The comparison of the residuals showed an error variance Se2 (0.0272), which indicates that none of the individual residual values exceed twice the square root of the residual variance [26].

Fig. 5. Normal probability plot of residuals for surface roughness.

Table 5 Observed responses and predicted values Standard order

Actual value

Predicted value

Residual

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

2.23 3.45 2.89 3 2.02 2.38 3.2 3.2 2.22 3 2.25 2.95 2.14 2.3 2.25 1.75 2.22 3.10 2.1 2.54 2.35 2.45 3.13 2.42 2.5 1.85 2.33 2.3 2.032 2.31 2.32 1.92256

2.1 3.32 2.87 3.1 2.18 2.27 3.06 3.04 1.96 2.75 2.18 2.86 2.16 2.69 2.26 1.8 2.36 3.12 2.06 2.5 2.49 2.14 3.27 2.44 2.5 2.06 2.28 2.28 2.28 2.28 2.28 2.28

0.13 0.13 0.021 −0.1 −0.16 0.11 0.14 0.16 0.26 0.25 0.068 0.094 −0.016 −0.39 −0.011 −0.049 −0.14 −0.022 0.042 0.044 −0.14 0.31 −0.14 −0.024 3.90E−03 −0.21 0.053 0.023 −0.24 0.033 0.043 −0.35

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All of the above consideration indicates an excellent adequacy of the regression model. Each observed value is compared with the predicted value calculated from the model in Fig. 6. It can be seen that the regression model is fairly well fitted with the observed values. The 3D surface graphs for surface roughness are shown in Fig. 7(a–d). Fig. 7(a–d) shows that the surface roughness of evaporative pattern castings of Al–7% Si alloy reduces with the increase in sand grainfiness number. This is due to the fact that the micro-configuration of the casting surface depends upon the phenomena occurring at the mold metal interface. In case of packing of sand grains of the same radius, the maximum height of asperites is limited to the radius of sand grains. If the size of the sand grains reduces, the height of asperities also reduces and hence surface roughness of the casting reduces. By increasing the sand grainfiness number, percent fines available in the sand mass increases. These fines settle in between the sand grains.

Fig. 6. Plot of actual vs. predicted response of surface roughness.

Fig. 7. (a–d) Effect of process parameters on the surface roughness.

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Thus, they reduce the height of the asperities in between the sand grains, and, in turn, the surface roughness of the casting reduces. Fig. 7(a and b) represents the surface roughness increases with the increase of level of vacuum imposed and pouring temperature. Vacuum pressure acts adversely to suck the molten metal into asperities generated at the mold metal interface. The higher the vacuum, the more will be the sucking phenomena in the capillaries formed among the sand grains. Which in turn increases the heights of asperities, hence increased surface roughness. The high superheat of the pouring metal reduces the surface tension of the molten metal, which further help in the sucking of metal into the capillaries formed among the sand grains. This increases the surface roughness of the castings. Fig. 7(c) shows that the surface roughness of the casting decreases with increasing amplitude of vibration up to the level of 485 ␮m. This is due to reason that as the amplitude of vibration increases, finer particles of the sand attain the mobility and they start settle down in between the sand grains. But at the higher amplitude of vibration above 485 ␮m the coarse particle get sufficient mobility and force themselves to move towards the surface of the pattern, there by increasing the size of the asperities at mold metal interface. As a result the surface roughness increases as the amplitude of vibration exceeds 485 ␮m. It can be observed from Fig. 7(d) that the surface roughness of the castings reduces with the increase of vibration time. The higher the vibrating time the more number of fines will settle at the mold metal interface, thus, reducing the height of the asperites there. 11. Conclusion The following conclusions have been obtained form the experimental study: • The degree of vacuum, pouring temperature, grainfiness number, amplitude of vibration and time of vibration has the significant effect. • Higher the grainfiness number, amplitude of vibration and time of vibration the better is the surface roughness of the castings. • Increase in degree of vacuum and pouring temperature has an adverse effect on the surface roughness. Acknowledgement The authors acknowledge the Department of Science and Technology, India for funding the above work. References [1] R.M. Monroe, Expendable Patterns Casting, American Foundryman Society Inc., 1992, p. 84.

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