Influence of Process Parameters on Microhardness of Electroless Ni-B Coatings

Abstract

Electroless Ni-B coatings have found large applications due to their high hardness and wear resistance. The present paper tries to investigate the influence of coating process parameters on the microhardness of electroless Ni-B coating with the help of Taguchi analysis. Four parameters, namely, bath temperature, concentration of reducing agent, concentration of nickel source, and annealing temperature, are considered and fitted into an $L_{27}$ orthogonal array to find out the optimized condition for improved hardness of the coating. The optimized condition is found to yield about 19% improvement in hardness of the coating compared to the initial condition. The significance of the process parameters and their interactions on the hardness of Ni-B coating is studied with the help of analysis of variance, which revealed that annealing temperature and concentration of reducing agent have significant influence over the hardness characteristics of electroless Ni-B coating. The compositional, microstructural, and phase structure analyses are conducted with the help of energy-dispersive X-ray analysis, scanning electron microscope, and X-ray diffraction analyzer, respectively.

1. Introduction

Coatings and finishes are becoming more important as problem solvers in a wide variety of industries. Completely new material concepts are successfully used, especially for coatings, to implement key optimizations of properties—often with reduced material consumption, with low technical effort, and at low process costs. Electroless nickel coating is one such coating technique that has been popularized in both scientific and industrial domains in the recent years [1]. Electroless coating is an autocatalytic process where the substrate develops a potential when it is dipped in electroless solution called bath that contains a source of metallic ions, reducing agent, complexing agent, stabilizer, and other components. Due to the developed potential, both positive and negative ions are attracted towards the substrate surface and release their energy through charge transfer process. Electroless Ni-P coating has already been widely accepted [1, 2], and the search for achieving a superior hard and wear-resistant surface has brought Ni-B coatings at the focus of research [3–5]. Electroless Ni-B coatings are widely used in aerospace and automotive industries particularly due to their high hardness and hence splendid wear resistance [6]. The hardness of electroless Ni-P and Ni-B coatings is dependent on the phosphorous and boron content, respectively. However, the hardness of electroless Ni-P increases with the decrease of phosphorous content, while the hardness of Ni-B increases with the increase in boron content of the coating [7]. Ni-B coatings are found to be harder than Ni-P coatings in as-deposited phase [3]. The hardness increases with heat treatment [8–10]. Krishnaveni et al. [4] studied the relationship between the microhardness of the electroless Ni-B coatings and heat-treatment temperature and reported two maxima in the hardness versus heat-treatment temperature curve, one at 350°C and the other at 450°C. Beyond 450°C, coatings began to soften as a result of conglomeration of the Ni₃B particles, and the hardness decreases. The increase of hardness of Ni-B coating with heat treatment is generally attributed to the modification of deposit structure allowing the precipitation of Ni-B phases according to the Ni-B phase diagram [10]. Dervos et al. [11] achieved a chromium equivalent hardness (more than 1600 HV) by heat treating the Ni-B films in high vacuum. The high hardness of electroless Ni-B plating has been utilized in the fabrication of micrometal molds [12]. Ni-B coating is also used to harden the surface of Ti-6Al-4V alloy through diffusion treatment of the former carried out by induction heating [13]. To improve the properties of Ni-B coatings, several composite coatings have been developed by incorporating diamond and silicon carbide particles [6]. Kaya et al. [14] have incorporated nanosized diamond particles into Ni-B coating to form such a composite coating which is found to be 30 and 14 times more wear resistant than steel and normal Ni-B coatings. Ni-B-Ti coating is used by Abdeli et al. [15] in order to increase the surface hardness of stainless steel. Search of improved tribological properties has led to the formation of duplex coatings of Ni-P and Ni-B [3, 16] and three-component coatings of Ni-B-P [17, 18]. As electroless nickel coatings fall in the category of thin coatings (hence, effect of substrate hardness may come into play) and also the surfaces are not prepared (smoothness is not ensured), Vitry et al. [19] compared the hardness measured by three different techniques (Vickers surface, indentation, Knoop cross-section indentation, and Berkovitch cross-section nanoindentation) and the values to be consistent.

Normally, a coating is developed based on the application in which it would be utilized. Based on the application scenario, the coating may need to possess properties such as high hardness, corrosion resistance, wear resistance, lubriciousness and smoothness, heat resistance, decorative properties, and electrical conductivity to name a few. Among these, hardness is the material property that is of high importance for technical applications. Surface hardness is especially critical for use in components and semifinished products in order to control wear and tear processes. This makes hardness a characteristic of materials that determines the safety and function of technical systems and constructions. This is why international research efforts in the field of hard materials, with its integral importance within the industrial value chain, are continuously looking to develop custom hard materials. Electroless Ni-B has already shown all the potentials to be such a coating material. Now, the properties of Ni-B coatings are found to be highly dependent on the composition of the bath from which it evolves [7]. Hence, the present study investigates the dependence of hardness characteristics of the coating on various bath compositions. However, a review of the existing literature revealed that the study of hardness of Ni-B coatings has mainly been confined to and around the effect of heat treatment on the coatings. To the best of the authors’ knowledge, scientific approaches to obtain an optimum bath formulation for an enhanced (maximum) hardness have remained unaddressed. Thus, the present paper is formulated into an optimization problem based on Taguchi method, so that the optimum bath composition for maximum hardness can be predicted and also the influence of the bath parameters on the hardness behavior can be better understood. Moreover, the coating is characterized with the help of SEM, EDX, and XRD in order to understand the microstructure characteristics of Ni-B coatings.

2. Taguchi Technique

A system or process, in general, is considered to be a combination of man, machine, method, and other resources that transform some input (substrate, chemicals, equipments, energy, manpower, etc.) into an output (deposited mass, composition, structure, properties, etc.) that has one or more observable responses. Some of the process variables are controllable (temperature, reducing agent, metal source, pH, bath load, etc.), that is, they can be easily set by the experimenter to vary the response as desired, whereas other variables are uncontrollable (errors in measuring instrument, quality of chemicals, ambient conditions, human errors, etc.) which are difficult or impossible to control. These variables are called noise factors and are beyond the control of the operator. Therefore, to reduce variation in the response, the process should be such that it is not affected by minor fluctuations in these factors. The process of making a system insensitive to noise factors is referred to as robust design. Robust design was pioneered by the Japanese industrialist, Dr. Genichi Taguchi, in the early 1980s [20–22].

In case of design of experiments (DOEs), Taguchi analysis relates the variability in the responses of a particular trial condition with the effect of the uncontrollable variables or noise. The basis on which Taguchi analysis searches for the optimal condition is by observing the reduction in variation of the results within a particular trial condition. Thus, to take variability into account, Taguchi analysis uses signal-to-noise (S/N) ratio to convert the output response into a value for the evaluation purpose. Again based on the criteria of the experiment, S/N ratio can be categorized as follows: lower the better (LB), higher the better (HB), and nominal the best (NB). For the present case of maximization of hardness, HB criterion needs to be used.

Taguchi's approach to achieve a high-quality system consists of three stages, namely, system design, parameter design, and tolerance design. System design consists of the stage when ideas for a new system are used to decide upon the combinations of factors to obtain a functional and economical design. Parameter design refers to the stage when factor settings are selected that make the system less sensitive to variations in the uncontrollable factors affecting the system. Hence, if this stage is carried out successfully, the resulting system will have little variation, and the resulting tolerances will be tight. Tolerance design refers to the final stage when tolerances are tightened around the best value. This stage increases cost and is only needed if the required quality is not achieved during parameter design. Thus, using parameter design, it is possible to achieve the desired quality without much increase in the cost. Taguchi also uses a set of orthogonal arrays (OAs) to learn the whole parameters space with only a small number of experiments. In the present study, an L₂₇ OA is used to study the effect of coating process parameters, as well as their interactions on the microhardness of electroless Ni-B coatings. Furthermore, to know which of the process parameters have a significant influence over the hardness of Ni-B coating, analysis of variance (ANOVA) [23] is also performed. Finally, to verify and validate the optimal condition obtained through OA design, a confirmation test is carried out, and the improvement in the hardness at the optimal condition is compared to the initial condition.

3. Experimental Details

3.1. Substrate Preparation

The preparation of the substrate is an important phase for the proper development of any coating on its surface. In the present study, plain carbon steel (AISI 1040) is used as a substrate material. Substrates are cut and sized to a dimension of 20 mm × 20 mm × 8 mm. The substrates are meticulously prepared so that their sizes are maintained with precision. The substrates, after preparation, are primarily washed with soap and water to clean the dust and foreign particles. Acetone is then employed to clean any remaining organic products. The substrates before coating are subjected to pickling treatment in dilute (18%) hydrochloric acid to ensure the removal of surface layer formed like rust or other oxides.

It can be noted here that hardness characteristics of Ni-B coatings may be dependent on the surface roughness of the coating, which may again be dependent on the surface roughness of the substrate. However, in the present case, the substrate roughness is assumed to be almost constant and hence not taken into account. Again achieving the same roughness in all the substrates is very difficult, especially as each one is machined separately. Thus, to solve this problem, a large number of substrates are prepared, and their roughness (centre line average, R_a) is evaluated. The samples which showed small variation in roughness are used for the deposition of electroless Ni-B coatings. A surface profilometer, Talysurf (Taylor Hobson, Surtronic 3+), is used to measure the roughness values of the substrates prior to the coating. The R_a values of the substrates are found to lie in the range 0.2–0.3 μm.

3.2. Coating Procedure

Borohydride-reduced baths are in general very unstable and difficult to control. Hence, the bath composition and the deposition conditions for the successful deposition of Ni-B coatings are selected after a large number of trial experiments. The selected bath composition is shown in Table 1. Nickel chloride supplies the nickel ions in the solution, while sodium borohydride is the reducing agent, reducing the nickel ions from their positive valence state to zero valence state. But as the reaction between nickel chloride and sodium borohydride is quite fast and intense, instant decomposition of the bath is inevitable. Hence, a complexing agent (Ethylenediamine) is required to slow down the reaction into a viable form. Ethylenediamine forms metastable complexes with nickel ions and releases them slowly for the reaction. But even after the addition of complexing agent, there remains a possibility of solution breakdown. Hence, a stabilizer (Lead nitrate) is needed so that the solution remains stable for the duration of the coating. As borohydride baths are operated at higher pH values, the pH of the present bath is maintained around 12.5 and continuously monitored with a digital pH meter. 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. The activated substrates are then submerged into the electroless bath maintained at 85–95°C (according to the OA), and the coating is carried out for a period of 2 hours. The coating thickness is found to lie in the range of 25–30 microns. After coating is over, the samples are cleaned with distilled water. As heat treatment is known to increase the hardness of electroless nickel coatings, the coated samples are annealed in a box furnace for 1 hr at different temperatures (250°C, 350°C, and 450°C) according to the OA. After annealing, the samples are cooled to room temperature (25°C) without the application of any artificial cooling.

Table 1:

Bath constituents and their ranges.

Parameters	Ranges of parameters

Nickel chloride	15–25 g/L
Sodium borohydride	0.6–1.0 g/L
Ethylenediamine	59 g/L
Lead nitrate	0.0145 g/L
Sodium hydroxide	40 g/L
Bath temperature	85–95°C
pH of solution	12.5

3.3. Choice of Design Parameters

Design parameters are nothing but control factors that can be suitably adjusted to modify the output response as desired. In case of electroless nickel coatings, it is found that the properties of the coatings are very much dependent on the bath composition and the deposition condition. But browsing through the existing literatures, it was revealed that researchers mainly used bath temperature (A), the concentration of reducing agent (B), and the concentration of nickel source (C) as the control parameters to modify the characteristics of the coatings. Hence, these three coating parameters are considered as the main design parameters in the present study. The two-way interaction effects among the factors are also considered. Moreover, annealing is found to have a great effect on the hardness of the coating. Thus, annealing temperature (D) is taken into account as the fourth parameter in the experimental design to study its effect on the hardness of the coating. The considered design parameters, together with their levels, are shown in Table 2. Consideration of three levels allows the study of nonlinear effects if any.

Table 2:

Design parameters and their levels.

Design factors	Unit		Levels
Design factors	Unit	1	2	3

Bath temperature (A)	°C	85	90 a	95
Reducer concentration (B)	(g/L)	0.6	0.8 a	1.0
Nickel source concentration (C)	(g/L)	15	20 a	25
Annealing temperature (D)	°C	250	350 a	450

: initial condition.

3.4. Response Variable

Response variable is the output of an experimental model. In the present study, maximization of the hardness of electroless Ni-B coatings is the main objective. Hence, the response variable used to accomplish this study is Vickers hardness number (HV_0.1). The coating parameters are optimized with the objective of maximizing the HV of electroless Ni-B coatings.

3.5. Design of Experiments

Design of experiments (DOEs) refers to the process of planning, designing, and analyzing the experiment so that valid and objective information can be drawn effectively and with greater efficiency. DOE is based on the objective of desensitizing a product's performance characteristic(s) to variation in critical product and process design parameters. In DOE, preplanned changes are made to the control variables in order to observe the corresponding effect on the response variable. As mentioned earlier, Taguchi method uses an OA (orthogonal array) to reduce the number of experiments for determining the optimal process parameters. The OA allows one to compute the main interaction effects via a minimum number of experimental trials [21]. Several standard OAs have been tabulated by Taguchi. For the present paper,L₂₇ OA is chosen based on the number of factors considered, their levels, and the desired interactions of the factors. The selected array requires the execution of 27 experiments. The factors (A, B, C, and D) and their interactions ( $A \times B$ , $A \times C$ , and $B \times C$ ) are assigned to their respective positions in the OA (as seen in Table 3) based on the triangular table for 3-level OA [22]. The cell values 1, 2, and 3 as seen in the main factor column in the array correspond to the lowest, medium, and highest levels of the factors. For the interactions, the same indicates the combination of the levels of the main factors concerned. For example, the interaction between A and B ( $A \times B$ ) exists in columns 3 and 4, and for trial 1, the concerned cells show 1 in column 3 and 1 in column 4. Hence, the interaction $A \times B$ has the value 11 which means it is the combination of level 1 of A and level 1 of B. Similarly, there are 9 such combinations (11, 22, 33, 12, 21, 23, 32, 13, and 31) for $A \times B$ interaction in columns 3 and 4. The cell values in interaction columns and error columns are used in ANOVA for determination of their percentage contribution to the total effect.

Table 3:

Design factors and interactions in $L_{27}$ orthogonal array.

Trial number	Column numbers
	1	2	3	4	5	6	7	8	9	10	11	12	13
	A	B	$A \times B$	$A \times B$	C	$A \times C$	$A \times C$	$B \times C$	D	—	$B \times C$	—	—

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

3.6. Microhardness Measurements

Hardness, as defined by material engineers, is the property of a material, which gives it the ability to resist being permanently deformed by another material, when a load is applied. The basic goal of hardness testing is to quantifiably measure the resistance of a material to plastic deformation. Hardness values offer a comparative measure of a material's resistance to plastic deformation from a standard source, as different hardness techniques have different scales. The Vickers hardness test is a commonly used test due to its wide load range capability. The hardness number is based on measurements made of the indent formed in the surface of the test specimen. Vickers hardness (HV) is calculated with an equation:

\begin{matrix} HV = \frac{1.8544 F}{d^{2}}, \end{matrix}

(1)

where load (F) is in kilograms force, and the mean of two diagonals created by the pyramidal indent (d) is in millimeters. Since, in the present study, the material in question is a thin Ni-B coating (25–30 μm), microhardness testing approach, using a precise diamond indenter and a low load (100 gram force), is employed. Microhardness testing of Ni-B coatings is carried out in a UHL microhardness tester (VMHT MOT, Technische Mikroskopie) with a Vickers diamond indenter. The dwell time is kept at 15 s while the speed of indentation is set at 50 μm/s. The microhardness tester is controlled via a touch-screen-based system which is part of the tester, and the impressions of the indentions are captured on a computer through a digital camera. The hardness numbers are obtained by processing the indention image through dedicated software installed on the computer. It should be mentioned here that as the hardness is measured just after the coating is over and no separate surface preparation is done, an average of at least five hardness values for each sample are reported. Also the indentation marks are captured by the digital camera and saved on the computer. A couple of indention marks for a specimen are shown in Figure 1.

Figure 1:

Optical micrograph of indentation marks.

It may be noted here that the indentation depth (h) is related to mean diagonal (d) by the relation $h = d / 7$ . In the present experiment, the maximum value of d is found to be around 15 μm. Hence, h is evaluated as $15 / 7 = 2.14$ μm. It can be seen that the depth of indention is very low compared to the thickness of the coating. This implies that the measured value of hardness represents the hardness of the coating itself with no effect of the substrate material coming into play.

3.7. 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 behaviour of the coating can be correlated with changes occurring at the microscopic level. The electroless Ni-B coatings developed in the present study are characterized as follows.

The surface topography of the coating is observed through scanning electron microscopy (SEM) in order to analyse the microstructure of the deposits before and after heat treatment at various temperatures to see the effect of heat treatment temperature.

Energy dispersive X-ray analysis (EDAX Corporation) is made use of in order to determine the composition of the coating in terms of the weight percentages of nickel and boron. It has been demonstrated by previous studies [7] that the hardness of the deposited film is greatly influenced by the concentration of boron in the film. This concentration in turn depends upon the amount of reducing agent added in the bath. Hence, EDX analysis is done on the coatings developed from the bath consisting of different concentrations of sodium borohydride (reducing agent) in order to capture the range of boron content in the coatings.

The phase structure is studied with the help of X-ray diffraction (XRD) analysis (Rigaku, Ultima III) so that the different precipitated phases both before and after heat treatment are identified.

4. Results and Discussion

4.1. Analysis of Signal-to-Noise Ratio

Signal-to-noise (S/N) ratio is a measure used in science and engineering to quantify how much a signal has been corrupted by noise. In respect of DOE, signal is interpreted as mean, while noise is interpreted as standard deviation. Taguchi employs S/N ratio to convert the experimental results into a value for the evaluation characteristic in the optimum parameter analysis. As the main objective of Taguchi technique is to reduce the variability in the results due to noise, it (Taguchi technique) tries to reach optimality by maximizing the S/N ratio so that the effect of noise is minimized. In the present work, S/N ratio analysis is done with HV_0.1 as the performance index. As hardness is to be maximized, the S/N ratio for HV_0.1 is calculated using HB (higher the better) criterion and is given by

\begin{matrix} S / N = - 10 \log (\frac{1}{n} \sum \frac{1}{y^{2}}), \end{matrix}

(2)

where y is the observed data, and n is the number of observations. The hardness values together with their S/N ratio values are shown in Table 4. As it is known that the columns of the OA are orthogonal to each other, the average effect of each factor on the quality characteristic at different levels can be determined. The average of the S/N ratio for each level of the factors of A, B, C, and D is given in Table 5. The delta value is calculated by subtracting the largest value from the lowest among the values in each column. The lager the delta value is, the greater impact the factor has on the process response. It is found from Table 5 that annealing temperature (D) possesses the highest delta value and hence has the greatest influence over the hardness of electroless Ni-B coatings. The main effect plot is illustrated in Figure 2. This plot shows the effects of changing the parameters from one level to another. The greater is the difference between the levels, the greater is the effect. The horizontal line in the plot represents the overall mean of the experimental region, which is the average of the S/N ratio of the twenty seven trials of the experimental matrix. From the plot, it can be clearly observed that parameter D has the largest difference between the levels and hence has the largest influence over the hardness of Ni-B coating. Parameters B and C are also found to have some influence over the hardness. But parameter A has the least influence over the hardness of the coating. Figure 3 shows the interaction plots. In case of interaction, nonparallelism of the plots is observed. Nonparallel lines are indicative of the presence of interaction, while intersecting lines are indicative of the presence of strong interaction. From the interaction plots (Figure 3), it is evident that lines intersect in all the plots, and hence, all the factors have some amount of interaction between each other. The main effect plot also gives the optimal combination of process parameters for maximum hardness. Since Taguchi method obtains the optimal level combination by choosing those levels for which S/N ratio is the highest, the optimal combination of parameters is found to be A3B3C2D2. The increased hardness of Ni-B coatings heat treated at D2 (350°C) is quite consistent with the findings of [24]. Also 350°C is a critical temperature of microstructure transformation as crystalline phases of nickel and nickel borides (Ni₃B and Ni₂B) form during this process, which is a key contributor to the hardness of Ni-B coating [25]. The same phenomenon may be happening in the present case but can be only be explicitly analysed by microstructure study of the coating. Again use of higher heat-treatment temperatures and longer times leads to the decrease in hardness, which may be attributed to the nickel grain growth and to the borides coarsening. Moreover, it has been observed in general that hardness of Ni-B coatings increases with the increase of boron content in the coating. Again boron content in the coating is proportional to the concentration of sodium borohydride in the electroless solution. Hence, the highest level of parameter B (B3) being part of the optimal condition is also in agreement with that found by other researchers [7].

Table 4:

Hardness and S/N ratio values.

Exp. number	Hardness (HV_0.1)	S/N ratio

1	912.25	59.2023
2	1087.50	60.7286
3	837.00	58.4545
4	965.33	59.6935
5	1063.00	60.5307
6	885.80	58.9467
7	1082.00	60.6845
8	941.30	59.4746
9	976.00	59.7890
10	1043.00	60.3657
11	937.60	59.4404
12	933.67	59.4038
13	838.60	58.4711
14	1018.40	60.1584
15	1011.00	60.0950
16	855.50	58.6444
17	1088.60	60.7374
18	1024.00	60.2060
19	913.40	59.2132
20	825.80	58.3375
21	1105.40	60.8704
22	892.60	59.0131
23	1018.20	60.1567
24	977.60	59.8032
25	1191.30	61.5204
26	1137.20	61.1167
27	911.80	59.1980

Table 5:

Table for mean S/N ratio.

Level	A	B	C	D

1	59.72	59.56	59.65	59.15
2	59.72	59.65	60.08	60.44
3	59.91	60.15	59.64	59.77
Delta	0.19	0.59	0.43	1.29
Rank	4	2	3	1

Total mean S/N ratio = 59.78725.

Figure 2:

Main effects plot for signal-to-noise ratio.

Figure 3:

Interaction effects plot for mean hardness: (a) A versus B, (b) A versus C, and (c) B versus C.

4.2. Analysis of Variance

The experimental data was subjected to analysis of variance (ANOVA) in order to understand the magnitude of influence that the process parameters had on the hardness of the coating. The results obtained through ANOVA with the S/N ratio as response is displayed in Table 6. The ANOVA table consists of F-ratio that is used to determine which of the process parameters have a significant effect on the characteristic quality. The F-ratio, for a given degree of freedom corresponding to any process parameter is defined as the ratio between the variance in the coating attribute due to change in the process parameter levels and the variance in the coating attribute due to experimental error. By comparing the evaluated F-ratio values with the tabulated ones, the significance of a particular factor or an interaction on the process response can be readily understood. If the obtained F-value of a parameter or interaction is greater than the tabulated one, then that particular parameter or interaction has a significant influence over the process response. From Table 6, it can be observed that parameter D (annealing temperature) has the most significant influence over hardness of Ni-B coatings and that too at a confidence level of 95%. Parameter B (concentration of reducing agent) is also significant but at a confidence level of 65%. From ANOVA, the percentage contribution of the factors and interactions is also calculated thereby giving an insight into the relationship between the variables and the hardness characteristics of the coating. The percentage contribution indicates the influence of the process parameter and their interactions on the coating attribute considered, with a larger percentage indicating a stronger influence. Present ANOVA table shows that parameter D has the largest contribution (38.04%) followed by parameters B (9.39%), C (5.73%), and A (1.11%). Among interactions, the highest contributor is $A \times C$ (13.09%) followed by $B \times C$ (10.09%) and $A \times B$ (4.75%) within the experimental range considered in the study.

Table 6:

Results of ANOVA for hardness.

Source	DOF	SS	MS	F	% Contribution

A	2	0.2181	0.1091	0.19	1.11
B	2	1.8397	0.9198	1.59 b	9.39
C	2	1.1229	0.5614	0.97	5.73
D	2	7.4516	3.7258	6.43 b	38.04
$A \times B$	4	0.9313	0.2328	0.40	4.75
$A \times C$	4	2.5656	0.6414	1.11	13.09
$B \times C$	4	1.9769	0.4942	0.85	10.09
Error	6	3.4792	0.5799

Total	26	19.5853

Significant factors and interactions $F_{0.05,2, 6} = 5.143$ ; $F_{0.35,2, 6} = 1.26$ .

4.3. Confirmation Test

Verification is an important stage to check whether, at all, any improvement in the process response is obtained with the optimum condition suggested by DOE analysis compared to the initial condition. This is known as the verification/confirmation test. The confirmation experiment is performed by conducting a test with optimal settings of the factors and levels previously evaluated. The predicted value of the S/N ratio at the optimum level $\overset{⌢}{η}$ is calculated as

\begin{matrix} \overset{⌢}{η} = η_{m} + \sum_{i = 1}^{o} ({\bar{η}}_{i} - η_{m}), \end{matrix}

(3)

where η_m is the total mean S/N ratio, ${\bar{η}}_{i}$ is the mean S/N ratio at the optimal level, and o is the number of main design parameters that significantly affect the hardness characteristics of electroless Ni-B coating. The results of the confirmation test in the present study are shown in Table 7. The middle level of the parameters ( $A 2 B 2 C 2 D 2$ ) is considered as the initial condition. The increase of the S/N ratio from the initial parameter combination to the optimal parameter combination is found to be 1.50352 dB. This means that hardness of Ni-B coatings increases by about 19% at the optimal condition compared to the initial one. In other words, the experimental results confirm that the prior design and analysis for optimizing the electroless coating parameters are suitably applied.

Table 7:

Confirmation test results.

	Initial condition	Optimal condition
	Prediction	Experimentation

Level	A2B2C2D2	A3B3C2D2	A3B3C2D2
Hardness (HV_0.1)	1053		1252
S/N ratio (dB)	60.44856	60.80472	61.95208

Improvement of S/N ratio = 1.50352 dB.

4.4. Compositional Analysis

The compositional analysis of the coating is conducted with one of the latest EDX detectors that do not contain any Beryllium window in order to detect light elements like boron. The Beryllium window if present absorbs all the soft X-rays thereby precluding the detection of lighter elements. The EDX plot is shown in Figure 4, and coating composition in terms of weight percentages is given in Table 8. The compositional analysis confirms that the content of boron in the coating increases with the increase of the concentration of sodium borohydride (reducing agent) in the electroless bath. Hence, the higher hardness observed in coatings developed with higher borohydride concentration (as pointed in Section 4.1) is rightly justified.

Table 8:

EDX results of Ni-B coatings.

Figure number	Conc. of NaBH₄ in bath	% of Ni	% of B	Total

Figure 4(a)	0.6 g/L NaBH₄	94.28	5.72	100
Figure 4(b)	1.0 g/L NaBH₄	92.54	7.46	100

Figure 4:

EDX plots of the coating: (a) 0.6 g/L NaBH₄ and (b) 1.0 g/L NaBH₄.

4.5. Morphology Study

The SEM micrographs of the coating surfaces in as-deposited and heat-treated (at 250°C, 350°C, and 450°C for one hour) conditions are shown in Figure 5. The surface exhibits a cauliflower-like structure with almost uniform distribution of Ni-B nodules. This may be happening due to the equiaxed growth of grains at the substrate interface which is probably induced by the high amount of nucleation sites on the substrate surface [26]. The surface of the Ni-B coatings appears to be dense and matte grey in colour with low porosity. Also by careful observation, it can be noted that the Ni-B nodules are quite deflated and flat in as-deposited condition but gradually grow in size with increase in heat treatment temperature giving rise to coarse grained structure.

Figure 5:

SEM pictures of Ni-B coatings: (a) asdeposited, (b) annealed at 250°C, (c) annealed at 350°C, and (d) annealed at 450°C.

4.6. Phase Structure Analysis

The major phases in the coatings both before and after annealing (at 350°C) are identified by X-ray diffraction analysis using Cu Kα radiation. The XRD analysis (Figure 6) shows that the Ni-B film is almost amorphous in as-deposited phase but turns crystalline with heat treatment. This is evident from the presence of microcrystalline peaks in as-deposited phase, whereas broad peaks of Ni, Ni₂B, and Ni₃B are found in samples heat treated at 350°C. Hence, the increased hardness of Ni-B coatings annealed at 350°C may be attributed to the precipitation hardening phenomenon [4]. The solid solubility of the coating changes with temperature to produce various nickel boride phases (as observed in XRD plots) which may be impeding the movement of dislocations (defects in crystal lattice) thereby contributing to the hardness of the coating.

Figure 6:

XRD plots of electroless Ni-B coating in (a) asdeposited and (b) annealed at 350°C.

5. Conclusion

Taguchi L₂₇array has been successfully employed to study the effect of the process parameters namely, bath temperature (A), reducing agent concentration (B), nickel source concentration (C), and annealing temperature (D), on the hardness of electroless Ni-B coatings. The optimized condition is found to be $A 3 B 3 C 2 D 2$ which yields about 19% enhanced hardness more than the initial condition. ANOVA results show that annealing temperature has the most significant (at 95% confidence level) influence on the hardness of the Ni-B coating. Also the concentration of reducing agent is found to be quite significant (at 65% confidence level) in influencing the hardness of the coating. Moderate amount of interaction is found to exist among all the factors. The boron content of the coating is found to lie in the range of 5.72–7.46. The SEM micrographs revealed that the coating possesses a cauliflower-like structure with no obvious surface damage and is of low porosity. The coating also appears to be dense and light grey in colour. The XRD plots showed that the electroless Ni-B coating is a mixture of amorphous and crystalline phase in as-deposited condition. But with heat treatment, the coating turns crystalline. This is ascertained by the presence of Ni₂B and Ni₃B peaks in the XRD plot of Ni-B coating heat treated at 350°C. The precipitation of these nickel boride phases may be contributing to the hardness of the coating.

Footnotes

Acknowledgments

The authors would like to acknowledge the research support provided by the Council of Scientific and Industrial Research, India: file no. 9/96(0621)2K10-EMR-I dated 05/03/2010 and Department of Science and Technology, India through PURSE program.

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