Process Design, Development and Mechanical Analysis of Cu-Zn Alloy Produced by Sand Casting Process

In this study, the process design, development and mechanical analysis of Cu-Zn alloy produced by sand casting process were carried out. The process parameter optimization was carried out using the Response Surface Methodology (RSM) with the process conditions in the following range: temperature (300-500 o C) and zinc content (5-25%) having the hardness and ultimate tensile strength as the response of the designed experiment. The raw materials were scraps of copper wire and zinc battery casing and 13 different compositions of the alloy were prepared having the total mass for each weight percentage weighing 1.5 kg. The results obtained indicated that the hardness and ultimate tensile strength increases with an increases in the zinc content but decreases with an increase in the temperature. The elongation was however found to increase with an in increase in temperature but with a decrease in the zinc content. It is envisaged that the findings of this work will assist the brass material developers and the end users in the development of products with excellent mechanical properties.


Introduction
The increasing quest for the materials with excellent properties capable of meeting the service and functional requirements has continued to trigger research interest in the field of materials development. The dynamic nature of technology, need for cost, energy and environmental sustainability as well as the changing products and industrial applications necessitate the development of materials with outstanding properties in order to meet these challenges. To a large extent, the quality of a product, cost effectiveness as well as its performance in service is a function of the materials employed for the development. Hence, the selection and the development of the right materials for the right application is a critical decision which affects the entire life cycle of a product from birth to the end of life. The motivation for this study stems from the quest to develop Cu-Zn alloy from scrap materials, thus, converting waste to wealth with improvement in the cost effectiveness of the final product. Cu-Zn alloy otherwise known as brass is a non-magnetic material which boast of good strength and ductility, high corrosion resistance, as well as good malleability and formability [1][2][3][4]. The alloy is made up of two principal materials namely copper and zinc in a varying proportion depending on the intended application with other elements such as aluminum, phosphorus, manganese, silicon, and arsenic in small compositions [5][6]. Due to its excellent properties, Cu-Zn alloy find suitable applications in the automotive industry, electrical and electronics industries, decorative purposes, plumbing services, amongst others [7][8][9][10]. Furthermore, the quest for materials which can promote cost, energy and environmental sustainability are another attraction to the alloy. This is because significant high strength to weight ratio of the Cu-Zn alloy can be achieved through a carefully balanced composition of the parent materials and other alloying elements. The development of materials with significant high strength to weight ratio is critical in minimizing the energy consumed and improving the environmental friendliness during the products' life cycle. Furthermore, cost, energy and environmental sustainability via the development of materials which can be reclaimed into service via a suitable end of life option once the product reaches its end of life. Previous study have proven that Cu-Zn alloy has high affinity for the recycling process due to its non-ferromagnetic behaviour [11][12]. This makes its separation from ferrous metal easy and the recovered Cu-Zn alloy can be recycled through the process of melting, casting and extrusion. The ease of recycling will promote cost effectiveness, and the concept of circular economy which emphasizes tolerance for waste generation during the product's life cycle with improvement in the material, energy and environmental conservation. Previous studies have shown that preliminary process design with use of the Design of Experiment (DoE) technique via the use of Taguchi, Response Surface Methodology etc. can be employed for the determination of the feasible combinations of process parameters that will enhance excellent mechanical properties [13][14][15][16]. Previous studies have also shown that the microstructure and mechanical properties of brass can also be enhanced with a carefully balanced composition of Cu-Zn and other alloying elements, addition of additives as well as the use of appropriate heat treatment technique [17][18]. Many innovative approaches aimed at improving the microstructure and mechanical properties of brass alloy have been reported [19][20][21]. For instance, Imai et al. [22] reported that the strength of Cu-Zn alloy (brass alloy) can be improved via the addition of small amount of chromium in solid solution as the strength impact of Cr solid solution in Cu-Zn alloy was reportedly significant as opposed to brass alloy strengthening via Cr precipitation. Okayasu et al. [23] reported that copper alloy with improved mechanical properties such as high strength and ductility can be obtained by the addition of alloying elements in the following compositions: Cu-Al9.3-Fe3.8-Ni2-Mn0.8 or Cu-Al4-Zn25-Fe3-Mn3.8 produced via warm rolling at 473 K. Furthermore, Hsieh et al. [24] reported that the microstructure of brass alloy can be enhanced via the addition of Bi and Pb as alloying elements produced via the gravity casting method. Xiao et al. [25] identified the method of cryogenic dynamic plastic deformation as suitable for strengthening Cu-Zn alloy but with reduction in ductility due to the appearance of shear bands. On the other hand, Jha et al. [26] explained that the ductility can be enhanced via heat treatment involving the annealing of the brass alloys at a controlled temperature. Mapelli and Venturini [27] found that heat treatment via annealing at elevated temperature can sufficiently increase the ductility of the brass alloy but with reduction in the strength of the material. In addition, in terms of wear resistance and creep performance, Wu et al. [28] found that the presence of Cu in the brass alloy can secure the development of an alloy with excellent wear resistance and creep performance for a carefully balanced composition. Other approaches such as cryo-rolling and Spark Plasma Sintering have also been reported to impact the mechanical and microstructural properties of Cu-Zn alloys [29][30][31]. However, there is still dearth of information regarding the combination of feasible process parameters that would promote excellent mechanical properties of brass alloy developed via the sand casting process. Hence, this is one of the focus of this work with the aim to establish a preliminary process design for the development of Cu-Zn alloy. In addition, the microstructural and mechanical properties of the developed samples evaluated will also assist manufacturers in the determination of the optimum range of process parameters. It is envisaged that the findings of this work will be beneficial to the brass materials developers and the industrial end users in the development of products with excellent mechanical properties whose life cycle will promote the concept of circular economy, as well as cost, energy, material and environmental sustainability. The succeeding sections present the materials and method employed in this study in order to achieve the set objectives as well as the discussion of the findings and the conclusion.

Materials and Method
The method used in the study is divided into two stages: numerical analysis and physical experimentation.

Numerical analysis
The design of experiment was carried out in order to optimize the process parameters. This was achieved using the Response Surface Methodology (RSM) and Central Composite Design (CCD).

RSM and CCD design and analysis
The design of experiment (DoE) was carried out using the Response Surface Methodology (RSM) and Central Composite Design (CCD). The RSM and CCD has the capability to identify the feasible combinations of process parameters and manufacturing conditions as well as their cross effects on the response of the designed experiment. In addition, the RSM can suitably study the interactive effects of the process parameters or conditions (independent variables) on the experimental response (dependent variables) [32][33][34]. For the purpose of this study, the annealing temperature and the percent content of the zinc were the two factors considered as the independent variables A and B respectively while the hardness and the tensile strength of the brass stand as the response (output) of the designed experiment. The RSM was further used for the correlation of the independent variables as a function of the dependent variables thus producing two mathematical models for the prediction of the hardness and the tensile strength of brass. The essence is to determine the optimum range of the process conditions that will bring about the development of material (brass) with excellent mechanical properties in addition to cost, energy, material and environmental sustainability. Using the design expert (version 8 software) the experimental design the Response Surface Methodology (RSM) and the Central Composite Design (CCD) produced 13 experimental matrices whose responses were determined via the physical experimentations. The summary of the experimentation design involving two factors varied over three levels: the high level (+1), centre points (0) and low level (-1) leading to the production of 13 samples of brass are presented in Tables 1 and 2.

Analysis of Variance
The statistical analysis of the mathematical model produced via the RSM and CCD was carried out using Analysis of Variance (ANOVA). The ANOVA evaluates the statistical significance of the output of the model. A good model which validates the numerical experimentation is signalled by a "p-value Prob > F" which should be less than 0.050, a F-value greater than unity, a "Lack of Fit" which is statistically insignificant relative to the pure error, the predicted R square, R squared and the adjusted R Squared which should be within the same range and close to 1 as well as the adequate precision which measures the signal to noise ratio which should be greater than 4 [16].

The physical experimentation
The physical experimentation is divided into two main stages; sand cast production and sample characterization 2.2.1 Sand casting process The choice of the sand casting process was informed by the fact Cu-Zn alloy has a relatively low melting temperature which makes the sand casting process quite feasible. The major raw materials were scraps of copper wire and zinc battery casing. Five (5) different compositions of the alloy were prepared as Cu -5%Zn, Cu -10%Zn, Cu -15%Zn, Cu -20%Zn and Cu -30%Zn alloy respectively, with the total mass for each percentage composition weighs 1.5 kg according to Table 3. The sequence of the casting process involved pattern making, mould and core making, casting, demoulding, removal of runner and cast cleaning as presented in Figures 1a-d. Tensile test samples of specifications 75 mm × 100 mm × 350 mm were machined from the lather and the samples were heat treated in an OMSZON electrical furnace whose temperature varies from 250-500˚C via homogenization annealing in order to homogenize the composition. Next, the grinding and polishing operations of each test sample were carried out.
While the grinding operation removes the marks and irregularities on the surface of the specimen, the polishing operations cleans and smoothens the surface so as to obtain a more precise mechanical and microstructural (metallographic) analysis of the samples. The polishing operations were carried out using ECONET II polishing deck with emery cloth mounted on a rotating disc. Each of the samples was held against the alumina impregnated cloth while the wear debris were removed under a constant flow of water. Furthermore, the polished surfaces were etched with ferric chloride solution for 30 seconds, and subsequently dipped in concentrated nitric acid in order to remove any inherent stains. Using a magnification of ×400, a ACCUSCOPE metallographic microscope was used for the metallographic examination of the samples.

Hardness
The hardness of the cast brass alloy samples were examined using the Monsanto Hounsfield Tensometer with 1. 5 mm diameter indenter ball and 100 kg load in accordance to ASTM E 384 standard. The hardness of the material is the measure of the resistance offered by the material against indentation hence the depth of the impression by steel ball indenter. Each of the samples were placed on the hardness testing table and allowed to make contact with the steel ball indenter and the diameter of the indentation was measured using the microscope and micrometer. The Brinell's hardness number (BHN) was calculated according to Equation Where: is the applied load (kg), is the diameter of the indenter (mm) and is the diameter of indentation (mm).

Ultimate Tensile strength
The ultimate tensile strength is the maximum load the specimen can carry before rupture or plastic deformation. The ultimate tensile strength of the cast brass alloy samples were examined using the Monsanto universal tensile testing machine under the application of increasing stresses at varying strain rates and temperatures. The tensile tests were carried out according to the ASTM D638 standard. The measurements of the specimens in terms of the diameter and length etc. were taken and recorded and the specimen was loaded into the Hounsfield universal tensile testing machine where it was loaded to 75% of yield to ensure the specimen is fully seated in the jaws. The load was therefore released and the mercury indicator was set. The loads were recorded until the specimen breaks and the percent elongation of the specimen was measured. The tensile stress which represents the strength the material can withstand before yielding to failure and the corresponding strain ( ) due to deformation from the load applied are expressed as Equations 2 and 3 respectively. Where; is the maximum load (kg) and is the cross-sectional area of the material (mm 2 ), is the final length (mm), is the initial length (mm) and − is the elongation. The area of the test pieces is the product of the nominal thickness and the width. Figure 2 presents the tensile strength specimen.

Results and Discussion
The experimental responses in terms of the hardness (BHN) and tensile strength using the combination of the process conditions given in Table 2 are presented in Table 4.

Results from the numerical experimentation
The statistical analysis of the results obtained from both the numerical and physical experimentations presented in Table 5 used to obtain a predictive model which correlates the dependent variables (hardness and tensile strength) as a function of the independent process parameters namely temperature and zinc content.
Where; is the temperature ( o C), B is the zinc content (%). Table 5 presents the statistical analysis of the mathematical model obtained for harness prediction. The model "F-value" (33.38) implies that the model is statistically significant, because there is only a 0.01% chance that the model "F-value" this large could occur due to noise. Furthermore, considering the value of the "p-value Prob > F" (<0.0001) which was significantly less than 0.050 indicates that the model terms are statistical significant. In this case, the significant model terms which can significantly influence the hardness of the cast brass alloy are A (temperature), B (zinc content), AB (the interactive effect of the temperature and the percent zinc content). The value of the correlation coefficients (R-Squared, Adjusted R-Squared Pred R-Squared) as well as the adequate precision are presented in Table 6. From Table 6, the values of R-Squared (0.9175), Adj R Squared (0.8901), Predicted R-Squared (0.8349) were within the same range and close to 1 which implies that the terms of the mathematical model are statistically significant. The closer the values to 1, the more significant the model terms and vice versa. In addition, the value of the adequate precision (17.294) which measures the signal to noise ratio is greater than 4, thus, indicating that the model significant for predictive purpose.  Figure 3 is the normal plot of the residuals for the developed model for hardness. This plot indicates the extent to which the data set is normally distributed. The data set were observed to be close to the average diagonal line thus indicating that the residuals are approximately linear although with inherent randomness left over within the error portion. The departure of data set points from the average diagonal line were minimal and found to be between the permissible range of ±10% in relation to the average diagonal line. The approximately linear pattern obtained is an indication of a normally distributed data set and the development of an accurate model which can be used for predictive and correlative purposes. On the other hand, the hardness of the samples were observed to decrease with an increase in the temperature. As the zinc content increases from 5%-25%, the corresponding hardness were also observed to increase from 42.3228 MPa to 75.5636 MPa. On the contrary, an increase in temperature to 500 o C reduces the magnitude of the hardness to 31.2424 MPa.   14876.57 12 The model "F-value" (43.73) implies that the model is statistically significant, because there is only a 0.01% chance that the model "F-value" this large could occur due to noise. Furthermore, considering the value of the "p-value Prob > F" ( < 0.0001) which was significantly less than 0.050 indicates that the model terms are statistical significant. In this case, the significant model terms which can significantly influence the hardness of the cast brass alloy are A (temperature), A 2 (the square of the temperature), and B (the percent zinc content). The value of the correlation coefficients (R-Squared, Adjusted R-Squared Pred R-Squared) as well as the adequate precision are presented in Table 8. From Table 8, the values of R-Squared (0.9683), Adj R Squared (0.9456) and Pred. R-Squared (0.8984) were within the same range and close to 1 which implies that the terms of the mathematical model are statistically significant. The closer the values to 1, the more significant the model terms and vice versa. In addition, the value of the adequate precision (87.001) which measures the signal to noise ratio is greater than 4, thus, indicating that the model significant for predictive purpose.  Figure 6 is the normal plot of the residuals for the developed model for the tensile strength. This plot indicates the extent to which the data set is normally distributed. The data set were observed to be close to the average diagonal line thus indicating that the residuals are approximately linear although with inherent randomness left over within the error portion. The departure of data set points from the average diagonal line were minimal and found to be between the permissible range in relation to the average diagonal line. The approximately linear pattern obtained is an indication of a normally distributed data set and the development of an accurate model which can be used for predictive and correlative purposes.

3.2
Effect of temperature variation on the ultimate tensile strength The evaluation of the effect of temperature were carried out at 300 o C, 400 o C, and 500 o C. From Figure 10, the ultimate tensile strength of the samples were observed to decrease with an increase in the temperature. This may be due to the fact that an increase in temperature above the recrytsllization temperature of the material often results in an increase in the grain size of the material thereby promoting the development of grain growth. The relationship between the tensile strength or hardness and grain size is inversely proportional. Large grain sizes brings about reduction in the tensile strength and hardness of the material and vice versa. The temperature increase promotes the dissolution of the brittle phase of the brass alloy as a result of homogenisation annealing with resulting increase in the ductility and toughness of the material. This is because the atom layers of the materials tend to break loose from the neighbouring bonds at increasing temperatures causing dislocation and free movement of the atoms thereby causing the reduction of internal residual stresses which improves the ductility and formability of the material but with reduction in the tensile strength and hardness [35].

3.2
Effect of temperature variation on hardness The evaluation of the effect of temperature were carried out at 300 o C, 400 o C and 500 o C. From Figure 11, the hardness of the samples were observed to decrease with an increase in the temperature. This may be due to the fact that an increase in temperature activates dislocation motion which promotes easy migration of the atom from the neighbouring bonds [36]. the percent zinc content. An increase in the percent content of the zinc up to 35% promotes the dissolution of the composition of the constituents' materials to form a homogenized solid solution. Further increase in the zinc composition between 35%-45% will bring about phase transition from the alpha to the intermediate alpha-beta phase and subsequently beta phase [37]. The dissolution of the composition of the constituents' materials to form a homogenized solid solution via an increase in the percent zinc content results in the development of materials with smaller grain size. The smaller the grain size, the higher the tensile strength and hardness of the material and vice versa.

Effect of zinc content variation on hardness
The evaluation of the effect of zinc content on the hardness of the samples was carried out at different zinc compositions: Zn-10%, Zn-15%., Zn-20%, Zn-25%. From Figure 13, the hardness of the samples were observed to increase with an increase in the percent zinc content. Zn-15% Zn-20% Zn-25% Figure 13. The hardness at varying zinc content

Effect of temperature variation on elongation
The evaluation of the effect of temperature were carried out at 300 o C, 400 o C and 500 o C. From Figure 14, the elongation of the samples were observed to increase with an increase in the temperature. This may be due to the fact that with an increase in temperature, the material deforms plastically thereby causing plastic flow with resulting increase in the elongation. Effect of zinc content variation on elongation The evaluation of the effect of zinc content on the elongation of the samples were carried out at different zinc compositions: Zn-10%, Zn-15%., Zn-20%, Zn-25%. From Figure 15, the elongation of the samples were observed to decrease with an increase in the percent zinc content. The increase in the percent zinc content promotes increase in the localization of the atoms of the constituents' material with resulting increase strength and reduction in the elongation. The results obtained for the elongation agree significantly with the findings of Lui et al. [38] on the investigation of the effects of annealing temperature and aluminum content on microstructures and properties of Al-brass.

Conclusions
The process design, development and mechanical analysis of Cu-Zn alloy produced by sand casting process were carried out in this study. The results obtained indicated that the hardness and ultimate tensile strength increases with an increases in the percentage of the zinc content but decreases with an increase in the temperature. The elongation was however found to increase with an increase in increase in temperature but with a decrease in the percent zinc content. It is envisaged that the findings of this work will be beneficial to the brass materials developers and the industrial end users in the development of products with excellent mechanical properties whose life cycle will promote the concept of circular economy, as well as cost, energy, material and environmental sustainability.

DECLARATION
 Ethical Approval: The study requires no ethical approval.  Consent to Participate: This is not applicable to this study.  Consent to Publish: This is not applicable to this study.  Zn-15% Zn-20% Zn-25%