Bikash Panja & Prasanta Sahoo* Department of Mechanical Engineering, Jadavpur University, Kolkata , India

Transcription

1 Indian Journal of Engineering & Materials Sciences Vol. 22, October 2015, pp Tribological behavior of electroless Ni-P coatings in alkaline environment and optimization of coating parameters using Taguchi based grey relational analysis Bikash Panja & Prasanta Sahoo* Department of Mechanical Engineering, Jadavpur University, Kolkata , India Received 25 September 2014; accepted 1 July 2015 Electroless nickel coating is an autocatalytic coating whose behavior is very much dependent on the composition of electroless bath. The present paper studies the synthesis of electroless Ni-P (nickel-phosphorous) coatings on mild steel substrate and optimization of the coating process parameters for minimum friction and wear in alkaline (NaOH) solution using Taguchi based grey relation analysis. The study is carried out using different combinations of four coating process parameters, namely, concentration of nickel source (A), concentration of reducing agent (B), deposition temperature (C) and annealing temperature (D) with three level each (1, 2 and 3). The wear and friction tests are conducted with a pin-on-disk tribometer. Taguchi based grey relational analysis is employed for the optimization of this multiple response problem using an L 27 orthogonal array. The optimal combination of parameters is found as A3B3C1D2. ANOVA is performed to find out the significance of the coating parameters and their interactions. Annealing temperature and deposition temperature are most influence in controlling friction and wear behavior. The surface morphology and composition of coatings are studied with the help of scanning electron microscopy (SEM), energy dispersed X-ray (EDX) analysis and X-ray diffraction (XRD) analysis. It is found that Ni-P coating is amorphous in as-deposited condition but gradually turns crystalline with heat treatment. The worn surface morphology reveals abrasive wear mechanism. Keywords: Electroless Ni-P coating, Tribological behavior, Alkaline environment, Optimization Most of the engineering components sustain rubbing action due to which wear takes place on the surface of the components and become useless after a certain period. Life and performance of these engineering components can be extended by applying hard coatings on the surface of the components. Among the various metallic coating procedures based on aqueous solutions, most metals are electroplated since electroplating is technically straightforward and less expensive than electroless deposition. Industrial use of electroless deposition method continues to increase due to its good anticorrosion, antifriction, and wear protection properties 1,2. The electroless plating deposition was proposed by Brenner and Riddell 3,4. Electroless Ni-P (EN) coating is an autocatalytic deposition of a Ni-P alloy from an aqueous solution onto a substrate without the application of electric current. It has got the ability to deposit uniformly on uneven surfaces or geometries. It provides a deposit that follows all the contours of the substrate without building up at the edges and corners. Electroless nickel coatings are used in different areas such as *Corresponding author ( psjume@gmail.com, psahoo@mech.jdvu.ac.in) aerospace, aviation, automotives, oil and gas processing, food processing, microelectronics, radio electronics, computer engineering, chemical processing, textiles, machinery, mining and metallization of plastic etc 5,6. The mechanical and tribological properties of EN coatings can further be improved by the incorporation of hard particles, with the help of heat treatment 7,8 and dry lubricants Heat treatment affects the properties of EN coatings by changing its microstructure 12,13. Friction and wear of EN coatings has been studied by number of researchers over the years The friction study of EN coating with a ramp apparatus concluded that coatings with high phosphorus content have higher friction coefficient than medium or low phosphorus electroless coatings 15. Wear performance of EN coating is greatly enhanced with heat treatment performed at 400 C for 1 h having the highest hardness 14,18. As harder materials generally encounter lesser wear, heat treated Ni-P coatings are found to be more wear resistant than the as-deposited ones. Recent studies have evaluated different mechanical and tribological characteristics of the coatings. Ni-P coatings are used in different environmental conditions. Typically it finds wide

2 504 INDIAN J. ENG. MATER. SCI., OCTOBER 2015 application in corrosive environments, viz., marine applications, chemical industry, petrochemical industry and chlor-alkali industry etc. In majority of these applications, the environment is alkaline in nature. However, to the best of the authors knowledge, no study is available in literature that reports the tribological characteristics of Ni-P coatings in such alkaline corrosive environment. Thus the present study considers friction and wear behavior of the coating in NaOH solution (10%) and optimization of coating process parameter for minimum friction and wear based on Taguchi methodology coupled with grey relational analysis. The surface morphology, composition, phase structure and wear behavior are studied with the help of scanning electron microscopy, energy dispersed X-ray analysis and X-ray diffraction analysis. Taguchi Method and Grey Relation Analysis The Taguchi technique 23,24 is a efficient tool for design of high quality system based on orthogonal array (OA) experiments that provide much reduced variance for the experiments with an optimum setting of process control parameters. The greatest advantage of this method is the saving of effort in conducting experiments; saving experimental time, reducing the cost, and discovering significant factors quickly. This robust design recommends the use of the loss function to measure the quality characteristic. The value of loss function is further converted into statistical measure which is called S/N (signal-to-noise) ratio. Taguchi s method uses S/N ratio which are logarithmic functions of desired output to serve as objective functions for optimization. Again based on the criteria of the experiment, S/N ratio can be categorized as: lower the better (LB), higher the better (HB) and nominal the best (NB). The parameter level combination that maximizes the appropriate S/N ratio is the optimal setting. For the case of minimization of friction or wear, LB characteristic needs to be used. Deng 25 introduced the grey system theory in Grey relation analysis is an efficient tool for such multi-response analysis. Grey relational analysis owes its origin to grey system theory. Any system in nature is not white (full of precise information), but on the other hand, it is not black (complete lack of information) either, and it is mostly grey (a mixture of black and white). The main objective of grey system theory is to supply information so that one can whiten the greyness. As a result, optimization of the complicated multiple performance characteristics is converted into optimization of a single grey relational grade. The optimal level of the process parameters is the level with the highest grey relational grade. In the present study, the grey relational grade is treated as the overall response of the process instead of the multiple responses of friction and wear. Furthermore, a statistical analysis of variance (ANOVA) is performed to find which process parameters are statistically significant 26. With the grey relational analysis and analysis of variance, the optimal combination of the process parameters is predicted. Finally, a confirmation test is conducted to verify the optimal process parameters obtained from the analysis. Experimental Procedure Preparation of substrate In the present study, Ni-P coating is deposited on solid cylindrical mild steel (AISI 1040) substrate of Ø4 mm 30 mm long. Turning, parting and grinding processes are employed for the preparation of the substrates. Now, as EN coatings normally follow the surface profile of the substrate, the substrates used for deposition in the present study should have similar surface roughness. Thus, roughness evaluations (center line average values, R a ) are carried out for all the substrates and the ones which showed as little as about 0.1% variation in roughness were selected for deposition. The roughness measurements are carried out using a surface profilometer (Taylor Hobson, Surtronic 3+). Coating procedure The substrates before coating are subjected to pickling treatment in dilute (18%) hydrochloric acid for one minute to remove rust and other oxide layers. Subsequently, the samples are rinsed in distilled water which is followed by methanol cleaning prior to coating. The selected bath composition and operating conditions for the deposition of the coating is shown in Table 1. EN deposition is carried out Table 1 Ingredients of electroless bath and their ranges Sl. No. Parameters Range of parameters 1 Nickel sulphate g/l 2 Nickel chloride g/l 3 Sodium hypophosphite g/l 4 Sodium succinate 12 g/l 5 Deposition temperature o C 6 ph of solution 4.5

3 PANJA & SAHOO: TRIBOLOGICAL BEHAVIOR OF ELECTROLESS Ni-P COATINGS 505 using nickel sulphate and nickel chloride as the source of nickel, sodium hypophosphite as the reducing agent and sodium succinate as the stabilizer. The ph value of the bath is maintained at the fixed value with the help of digital ph meter by adding required quantity of dilute hydrochloric acid. The substrates, prior to coating are activated by dipping into a warm (55 C) palladium chloride solution. This step is necessary to kick start the deposition on the substrate as soon as it is placed inside the electroless bath for deposition. The coating is carried out for a total period of 4 h so that a considerable coating thickness can be achieved which is necessary for carrying out the tribological tests. After 2 h of deposition, the specimen is taken out, rinsed with distilled water and then again placed in a freshly prepared bath for another 2 h. Deposition time is kept constant for all specimens so that the coating thickness remains approximately constant. The coating thickness is found to lie around 50 µm which is obtained by observing a neatly cut coated specimen section under SEM (Fig. 1). After coating is over, the samples are washed with distilled water. The coated specimens are annealed in a box furnace for 1 h at different temperature (300 C, 400 C, and 500 C) according to the L 27 OA. After heat treatment, the samples are remained place into the furnace to cool them up to ambient temperature without the application of any artificial cooling. Coating characterization Characterization of the coating is important, as it can ensure the proper development of the coating by getting an insight into its microstructure. Also the macroscopic behavior of the coating can be correlated with changes occurring at the microscopic level. Surface morphology study of the EN coating is done by SEM (JEOL, JSM-6360) to analyze the Fig. 1 Micrograph for cross-section of EN coating microstructure of the deposited coatings before and after annealing at various temperatures. SEM is also done after tribological testing to see the wear track patterns. EDX analysis (Inca, Oxford) is done in conjunction with SEM to study the composition of the EN coatings in terms of the percentages of nickel and phosphorous. The phase structure is studied with the help of X-ray diffraction (XRD) analysis (Rigaku, Ultima III) so that the different precipitated phases both pre and post heat treatment are identified. Design of experiment Design of experiments (DOE) is a technique to obtain the maximum amount of conclusive information from the minimum amount of work, time, energy, money, or other limited resource. The information generally comprises the relationship between product and process parameters and the desired performance characteristic. By learning and applying this technique, it is possible to significantly reduce the time required for experimental investigations. Orthogonal arrays (OA) are used to aid in the design of an experiment. There are a number of design factors that can affect the tribological behaviour of EN coatings. The design factors and their levels considered in this study are shown in Table 2. It is a four-factor three-level experiment, so the total degree of freedom (DOF) considering the individual factors and their interaction is 20. Here, L 27 OA is chosen as it satisfies all the DOF conditions. The selected array requires the execution of 27 experiments. The factors (A, B, C and D) and their interactions (A B, A C and B C) are assigned to their respective positions in the OA. Response variables are the output of an experimental model. The present study tries to minimize the friction and wear of EN coating. The coefficient of friction (COF) and wear depth (in microns) are taken as the response variables. Grey relational analysis is employed for further processing and converting both the responses (friction and wear) into a single grey relational grade. Design factors Table 2 Design factors and their levels Unit Levels Concentration of source of nickel (A) (g/l) Concentration of reducer agent (B) (g/l) Deposition temperature (C) o C Annealing temperature (D) o C

4 506 INDIAN J. ENG. MATER. SCI., OCTOBER 2015 Wear and friction test in corrosive environment Wear and friction characteristic of EN coated sample are carried out in alkaline environment (10 % NaOH solution) at room temperature. Wear and friction tests are conducted in tribometer (TR-208- M2, Ducom, India) using a pin-on-disk configuration. The coated samples dish up as test sample which are held perpendicular against a rotating alumina disk (Ø100 mm 8 mm thickness). As the hardness of alumina disk is 1680 HV 1, which is higher than the hardness of EN coated sample (maximum microhardness value ~ 800 HV 1 ). Thus wear will take place only in test specimens. Normal load is applied by placing dead weights on loading pan. The depth of wear is measured by a LVDT (Syscon) which has a measurement range of ± 2 mm with accuracy of 0.1 ± 1% µm. The frictional force is measured by a frictional force sensor (IPA) that uses a beam type load cell of range 0 to 100 N with accuracy of 0.1 ± 2% N. The experiments are conducted with a constant load of 20 N as well as sliding velocity m/s and for a constant time of 10 min considering the small coating thickness. Experimental data of wear and friction test are shown in Table 3. It is found that the maximum wear depth encountered is less than the coating thickness which implies that the coating does not undergo through-thickness wear. Results and Discussion Surface morphology study The SEM micrographs of coating surfaces in as-deposited and heat treated (at 300 C, 400 C and 500 C for 1 h) conditions are presented in Fig. 2. From the SEM micrographs of these surfaces, it is Table 3 Experimental results for wear depth and friction coefficient Exp. No. Wear (µm) COF Exp. No. Wear (µm) COF Exp. No. Wear (µm) COF Fig. 2 SEM picture of EN coating (a) as-deposited, (b) annealed at 300 o C, (c) annealed at 400 o C and (d) annealed at 500 o C

5 PANJA & SAHOO: TRIBOLOGICAL BEHAVIOR OF ELECTROLESS Ni-P COATINGS 507 seen that there are many globular particles on the surface of the substrate. The surface is optically smooth and of low porosity. No obvious surface damage is found. The surface of the EN coatings appears to be dense. Also by careful observation, it can be noted that the Ni-P nodules are quite deflated and flat in as-deposited condition but gradually grow in size with heat treatment up to a temperature of about 400 C. At 400 C, the surface of the coating attains a coarse grained structure. However, with further increase in temperature at 500 C, the coating turns bluish which may be due to the precipitation of nickel oxides and nickel phosphides. This observation is in line with the information available in literature 5. Compositional study The nickel phosphorous coating has been thoroughly inspected to evaluate the compositional characteristics of Ni-P coating on the base metal. The coated samples are characterized before and after heat treatment with the help of energy dispersed X-ray micro-analyzer (EDX) coupled to SEM. From this characteristics study the surface composition of nickel and phosphorous of the electroless Ni P deposits are determined. Table 4 shows the surface composition of the deposits. It may be mentioned here that no significant variation in surface composition is observed with varying annealing temperature. Phase structure study The major phases in the coatings both before and after heat treatment are indentified by XRD analysis Cu-K α radiation. Figure 3 indicates the XRD plots asdeposited and annealed (400 C) condition. From the figure, it is evident that in as-deposited condition the phase is mostly amorphous but turns crystalline with heat treatment. The major peaks of Ni 2 P, Ni 3 P and Ni 5 P 4 are found in heat treated specimen. Hence, the Ni-P coating changes with temperature to produce various nickel phosphide compound (as observed in XRD plots) which may be impeding the movement of dislocations thereby contributing to the hardness of the coating. Hardness study is conducted in order to know the effects of the process parameters especially heat treatment on the hardness of electroless Ni-P Table 4 EDX results of Ni-P coatings Type of coatings Wt% Ni Wt% P Total coating. Coated samples are prepared by the same range of bath constituents. The hardness is compared between as-deposited coatings and heat treated coatings with three different annealing temperatures (300 o C, 400 o C and 500 o C). The values of hardness obtained for as-deposited and heat treated coatings are as following: 564 HV 1 (as-deposited), 675 HV 1 (300 C), 790 HV 1 (400 C) and 743 HV 1 (500 C). Hardness values are higher for heat treated coatings compared to as-deposited coating. The increase in hardness may be attributed to fine Ni crystallites and hard inter-metallic Ni 3 P particles precipitated during the crystallization of the amorphous phase. The hardness is found to increase with annealing temperature up to 400 C after which it decreases due to grain growth and coarsening. Grey relation analysis for tribological behaviour Grey relation analysis is an efficient tool for such multi response analysis. The final response needed for processing with Taguchi analysis is the grey relation grade which is obtained through the following step of calculation. The first stage is to perform the grey relation generation in which the experimental results are normalized data in the range between 0 and 1. Then the second stage is to calculate the grey relational coefficient from the normalized data to represent the correlation between the desired and actual experimental data. In the final stage, the overall grey relational grade is calculated by averaging the grey relational coefficient corresponding to each Deposited Heat treated (400 C) Fig. 3 XRD plots for EN coating

6 508 INDIAN J. ENG. MATER. SCI., OCTOBER 2015 performance characteristic. Overall evaluation of the multiple performance characteristics is based on the calculated grey relational grade. As a result, optimization of the intricate multiple performance characteristics is converted into optimization of a single grey relational grade. The final response needed for processing with Taguchi analysis is the grey relational grade which is obtained through the following set of calculations: Grey relation generation In the present study as COF and wear are to be minimized, the normalized data processing by minimum value is adopted with help of lower-thebetter criterion. It can be expressed as max y i ( k ) y ( k ) i x ( k ) = i max y i ( k ) min y i ( K ) (1) Where x i (k) is the value after the grey relational generation while min y i (k) and max y i (k) are respectively the smallest and largest values of y i (k) for the k th response: wear depth (k = 1) and COF (k = 2). The proposed normalized data after grey relation generation are given in Table 5. Grey relational coefficient Grey relational coefficients are calculated to express the relationship between the ideal (best = 1) and the actual experimental results. The grey relational coefficient ξ i (k) can be calculated as ( k ) + r min max ξ i = (2) 0i ( k ) + r max where 0i = x 0 (k) - x i (k) = difference of the absolute value between x 0 (k) and x i (k), min and max are respectively the minimum and maximum values of the absolute differences ( 0i ) of all comparing sequences and r is the distinguishing coefficient which is used to adjust the difference of the relational coefficient, usually r Є {0, 1} 22. The distinguishing coefficient weakens the effect of max when it gets too big, enlarging the different significance of the relational Exp. No. Table 5 Grey relation analysis for wear depth and friction coefficient Normalized data Values of 0i Grey relation coefficient (ξ) Wear COF Wear COF Wear COF Grey relation grade Order

7 PANJA & SAHOO: TRIBOLOGICAL BEHAVIOR OF ELECTROLESS Ni-P COATINGS 509 coefficient. The suggested value of the distinguishing coefficient, r, is 0.5, due to the moderate distinguishing effects and good stability of outcomes. Therefore, r is adopted as 0.5 for further analysis in the present case. The values of 0i and the grey relational coefficient results for the experimental data are also shown in Table 5. Grey relational grade and ordering In the grey relational analysis, the grey relational grade is used to show the relationship among the series. The overall multiple response characteristics evaluation is based on grey relational grade α i which is calculated as follows: α = i 1 n ξi n k = 1 ( k ) (3) where n is number of process response. Higher the grey relation grade, the closer is the experimental value to the ideal normalized value. Thus the higher relational grade implies that the corresponding parameter combination is closer to the optimal. The combination yielding the highest grey relational grade is assigned the highest order while the combination yielding the minimum grade is assigned the lowest order. Values for the grey relational grade and their order are also listed in Table 5. Analysis of signal-to-noise ratio Taguchi method employs S/N ratio to convert the experimental results into a value for the evaluation characteristic in the optimum parameter analysis. In this study the responses are coefficient of friction and wear depths which are to be minimized for many engineering purposes. Here signal means desirable value (arithmetic mean) and the noise is the undesirable value (standard deviation). A larger S/N ratio represents a better quality characteristic because of the minimization of noise and the corresponding process parameters are incentive to the variation of environmental conditions and other noise factors. The variability can be easily captured if S/N ratio is used to convert the experimental results into a value for the evaluation characteristic in the optimum parameter analysis, instead of the mean. The idea is to maximize the S/N ratio, thereby minimizing the effect of random noise factors, which have a significant impact on the process performance. As both the responses, i.e., wear depth and coefficient of friction are to be minimized, for this reason the S/N ratio analysis is done with grey relation grade as the performance index. As grey relation grade is to be maximized, the S/N ratio is calculated using HB (higher the better) criterion and is given by Eq. (4). S 1 1 = 10log 2 N n y (4) where y is the observed data and n is the number of observation. The S/N ratio is preferred to the traditional means as the former can capture variability within the trial condition. The average of grey relation grade of each level of the factors of A, B, C and D is given in Table 6 and total average value of grey relation grade of all the 27 experiments is also listed in this table. From the response table it is found that process parameter D has the highest delta value (rank 1). Hence, annealing temperature has the maximum influence on minimum friction and wear of EN coatings in alkaline solution. Parameter B is also found to have moderate influence on the friction force and wear. Figure 4 shows the main effect plot of grey relation grade. The main effect plot gives the optimal combination of coating parameters for minimum friction and wear. As the larger the grey relation grade is, the closer will be the product quality to the ideal value. Hence, the optimal combination of parameters is found to be A3B3C1D2. So far as the interaction plots are concerned, estimating an interaction means determining the non-parallelism of parameter effects. Thus, if the lines on the interaction plots are non-parallel, interactions occur and if the lines cross, strong interactions occur between parameters. Figure 5 shows the interaction plots that reveal the fact that there is some interaction between the parameters in controlling the friction and wear behavior of EN coatings in alkaline solution. However, more quantitative comparisons can be revealed by ANOVA which is conducted in the following section. Analysis of variance (ANOVA) The main purpose of the analysis of variance (ANOVA) is the application of a statistical method to Table 6 Response table for grey relation grade Level A B C D Rank Delta Total mean grey relation grade =

8 510 INDIAN J. ENG. MATER. SCI., OCTOBER 2015 Fig. 4 Main effects for grey relation grade identify the effect of individual factors on the process response. The method is very useful for revealing the level of significance of influence of factors or interaction of factors on a particular response. It separates the total variability of the response into contributions of each of the factors and the error. The results obtained through ANOVA with the grey relation grade as response is displayed in Table 7. ANOVA calculates the F-ratio between the regression mean square and mean square error. This ratio is used to measure the significance of the parameters under investigation with respect to the variance of all terms included in the error term at desired significance level α. If the calculated value of F-ratio is higher than the tabulated value of F-ratio, then the factor is significant at desired α level. From Table 7, it can be observed that parameter D (annealing temperature) has the most significant parameter over friction and wear of EN coatings in alkaline solution with confidence level of 99.5%. Parameter B and C (concentration of reducing agent and deposition temperature) are also significant but at a confidence level of 95% and 90%, respectively. From ANOVA, the percentage contribution of the factors and interactions are also calculated thereby giving an insight into the relationship between the variables and the friction and wear behavior of the coating. Present ANOVA table shows that parameter D has the largest contribution. Similarly, the parameter B and C as well as interacting parameter B C have moderate contribution on friction and wear of the coatings within the experimental range considered in the study. Fig. 5 Interaction plot for mean of grey relation grade (a) A vs B, (b) A vs C and (c) B vs C Confirmation test After the optimal level of testing parameters have been found, it is necessary that verification test is carried out in order to evaluate the accuracy of the analysis and to validate the experimental results.

9 PANJA & SAHOO: TRIBOLOGICAL BEHAVIOR OF ELECTROLESS Ni-P COATINGS 511 Table 7 Results of ANOVA for grey relation grade Source DOF Sum of square Mean of square F-ratio % contribution A B * C * 9.43 D * A B A C B C Error Total *Significant parameter F 0.005,2,6 = 14.54; F 0.05,2,6 = 5.14; F 0.1,2,6 = 3.46 Table 8 Results of confirmation test Initial condition Optimal condition Prediction Experimentation Level A2B2C2D2 A3B3C1D2 Wear depth (µm) COF Grade Improvement of grey relation grade = Fig. 6 SEM picture of worn surface of EN coating Table 8 shows the comparison of the estimated grey relation grade with the actual grey relation grade using the optimal parameters. The improvement of grey relation grade from initial to optimal condition is which is about 65% of mean grey relation grade and it is a significant improvement. Study of wear mechanism SEM micrograph of the EN coated worn surface after wear testing is shown in Fig. 6. It is clear from the figure that load is taken by most of the nodules. The worn surface is composed of mainly longitudinal grooves all over the surface. This is indicative of the occurrence of micro-cutting and micro-ploughing effect and characterized as ductile failure. Hence, it can be concluded that the abrasive wear is the predominant phenomenon. The same trend is observed for other combinations of deposition parameters within the experimental regime considered in this study. Conclusions The coating process parameters (nickel source concentration, reducing agent concentration, deposition temperature and annealing temperature) are optimized in order to minimize the friction and wear of electroless Ni-P coatings in alkaline solution against rotating alumina disk. Taguchi based grey relational analysis is successfully employed in conjunction with Taguchi design of experiments to optimize this multiple response problems. It is seen that annealing temperature, reducing agent concentration and deposition temperature have the most significant influence in controlling friction and wear behavior of electroless Ni-P coating. The interaction of reducing agent concentration and deposition temperature has moderate contribution in controlling friction and wear of this coating. The optimal coating parameter combination for minimum friction and wear is obtained as A3B3C1D2, i.e, highest levels of nickel source concentration and reducing agent concentration, lower level of deposition temperature along with middle level of annealing temperature. The improvement of grey relation grade from initial to optimal condition is which is about 65% of mean grey relation grade. It is observed that surface of the coatings is smooth, of low porosity and dense with nickel and phosphorous content of around 90.5% and 9.5%, respectively. The coatings are amorphous in asdeposited condition but after heat treatment, the coating turns to crystalline with different nickel phosphide compounds. The pattern of the sliding

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