J Mech Behav Mater 2017; aop S. Gnanasekaran*, G. Padmanaban, V. Balasubramanian, Hemant Kumar and Shaju K. Albert Optimizing the laser parameters to attain maximum hardness in nickel based hardfacing surfaces https://doi.org/10.1515/jmbm-2017-0020 Abstract: In this investigation, an attempt has been made to optimize the laser hardfacing (LH) parameters such as power, powder feed rate (PFR), travel speed and defocusing distance to maximize hardness of Ni-based hardfacing surfaces. Statistical tools such as the design of experiments (DoE), analysis of variance (ANOVA) are used to develop the empirical relationship to predict the hardness of the deposits at the 95% confidence level. Response graphs and contour plots are constructed using response surface methodology (RSM) concept. From this investigation, it is found that the maximum hardness of 820.48 HV could be achieved for the deposit made using a power of 1314 W, PFR of 9 g/min, a travel speed of 366 mm/min, and a defocusing distance of 32 mm. Keywords: analysis of variance; austenitic stainless steel; design of experiment; hardness; laser hardfacing; optimization; response surface methodology. 1 Introduction Surface modification of traditional materials (steels, aluminum alloys, titanium alloys, etc.) by laser hardfacing (LH) is attracting more and more due to its momentous growth in industrial applications. Laser surface modification is carried out by intruding the laser energy on the substrate with the addition of desired peripheral ingredients (powder). This results in high-performance *Corresponding author: S. Gnanasekaran, Centre for Materials Joining and Research (CEMAJOR), Department of Manufacturing Engineering, Annamalai University, Annamalainagar-608002, Tamil Nadu, India, e-mail: gnanas[email protected] G. Padmanaban and V. Balasubramanian: Centre for Materials Joining and Research (CEMAJOR), Department of Manufacturing Engineering, Annamalai University, Annamalainagar-608002, Tamil Nadu, India Hemant Kumar and Shaju K. Albert: Materials Technology Division, Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam-603102, Tamil Nadu, India exteriors (high in wear, oxidation resistance, corrosion and fatigue) on a low-priced low-alloy bulk material with reduced metal cost and rare alloy elements. The laser energy can also be effortlessly tuned to obtain the anticipated surface properties [1–3]. An extensive demand for materials with improved properties in terms of their hardness and their resistance to wear, corrosion, and oxidation has been the driving force for the development of various surface hardfacing techniques and materials. Recently, LH has been explored for the deposition of less diluted and fusion-bonded thick and thin metallic coatings on a wide variety of metallic substrate materials with a low heat input. Austenitic stainless steels (AISI 316 LN) are widely used in nuclear reactors owing to their excellent corrosion resistance. However, their low hardness leads to poor surface properties in terms of wear and fatigue resistant which confine many of their industrial applications [4, 5]. Abundant studies have shown superior characteristics of hardfacing alloys deposited by laser surfacing compared to other conventional surfacing techniques [5, 6]. The LH technique has the benefit of depositing a precise thickness of the material on a selected area of the substrate. Cobalt- and nickel-based intermetallic alloys have been developed as an excellent corrosion- and wearresistant material over a wide range of temperatures and environments [7]. Nickel-based alloys are strengthened by the presence of large volume fraction of hard intermetallic laves phase in a much softer solid-solution phase or a eutectic phase mixture [8]. Therefore, tribology is seldom applied in bulk form, but rather are applied as coatings [9, 10]. Cobalt-base alloys have been extensively studied as overlays by laser cladding technique [11] as well as thermal spray technique [12]. Hemmati et al. [13] reported that dilution of the hardfaced deposit is influenced by laser power. Percentage of dilution is 5, 10, 15, 25, 30 and 35%, respectively. It is discovered that for Fe content rises, borides start to alteration in morphology and slowly reduce. Also, significantly lower amounts of Ni-Si-B eutectic phase’s form because of more Fe content. Abolition of the strengthening precipitates let’s to lower the hardness of the deposits (800–500 HV). Ming et al [14] investigated the Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM 2 S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel Table 1: Chemical composition (wt%) of substrate material (AISI 316LN). C 0.020 Ni Cr Mo Si Mn Cu Nb S P W 12.55 17.27 2.35 0.29 1.69 0.047 0.02 0.027 0.026 0.03 effect of powder feed rate (PFR) and translation speed (TS) of a laser cladding with three nickel-based hardfacing powders. Deposits produced at higher PFRs registered a higher hardness than deposits made with lower PFRs. Higher PFR produces a higher percentage of hard phases and, the percentage of hard phases decreases linearly with increasing TS. Zhang et al. [15] attempted a hardfacing by Colmonoy 6 powder on 316 L austenitic stainless steel using CO2 laser process. They investigated the effects of laser power, traveling speed, defocusing distance, PFR on bead height, bead width, penetration depth and dilution. They found that preheating is essential for preventing cracking in the LH procedure and 450°C is the suitable preheating temperature. The friction and wear test results showed that the friction coefficient of specimens with laser cladding is lower than that of specimens without laser cladding, and the wear resistance of specimens has been increased 53 times after laser cladding, which reveals that laser cladding layer plays a major role in wear resistance. The microstructures of laser cladding deposit are composed of Ni-rich eutectic, boride and carbides. It is well known that the hardfacing parameters plays a major role in determining the deposit quality as the process facts have not been disclosed so far and hence, the selection of LH process parameters to nickel-based alloys is very difficult. Response surface methodology (RSM) is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response of one interest is influenced by several variables and the objectives are to optimize this response [16]. In this investigation, RSM was used to reduce the number of experiments and optimize the process parameters that yield the higher hardness. It is understood that the hardfacing process parameters play a major role in deciding the quality of the deposits. Very limited investigations have been carried out to understand the effect of individual LH parameters on mechanical properties and microstructural characteristics. There is no literature available in optimizing the LH parameters to attain maximum hardness on nickel based hardfaced deposit on 316 LN austenitic stainless steel. Hence, in this study, an attempt has been made to optimize the important LH parameters to attain maximum Fe Bal hardness in nickel based hardfaced deposits on 316 LN austenitic stainless steel by RSM. 2 Experimental work 2.1 Identify important LH parameters The chemical composition of base metal and hardfaced powder are presented in Tables 1 and 2, respectively. The important LH parameters were identified and selected from the literature [15–17]. They are power (P), powder feed rate (F), travel speed (T), defocusing distance (D). Table 3 shows the physical properties of Colmonoy – 5 powder used for LH. Laser hardfacing system consists of solid state disc laser Trumpf TruDisk 4002, model which emits wavelength of 1030 nm and maximum available power is 4 kW. 2.2 Feasible working range of LH parameters Trial runs were carried out using 12 mm-thick 316 LN austenitic stainless steel plate and nickel based alloy to find out the feasible working limits of LH parameters. The optimization process was carried as per the flow chart (Figure 1). Different combinations of parameters Table 2: Chemical composition (wt.%) of hardfaced powder (Colmonoy-5). C 0.41 Fe Cr Si B O 3.10 10.44 4.02 2.26 0.03 Ni Bal Table 3: Physical properties of hardfaced powder. Flow rate (s/50 g) 16 App. density (g/cm3) Hardness (HRC) Particle size (mesh) μm 4.50 51–54 ±45 to 180 Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel 3 Figure 1: Flow chart for process optimization. were used to carry out the trial experiments. This was done by varying any one of the factors from minimum to maximum while keeping the other parameters at constant (Table 4). The feasible working limits of the individual parameters were identified by macrostructure (cross section of the deposits). A deposit which showed, a smooth appearance without any visible macro level defects such as crack, pores was chosen as the feasible working parameter. The chosen levels of the selected process parameters with their units and notations are presented in Table 5. 2.3 LH experiments and hardness evaluation Figure 2 shows the multi-track hardfaced deposit configuration with 50% overlapped used in this investigation. The base metal composed of fully elongated austenitic grains. The LH deposits were made as per the conditions dictated by the design matrix (Table 6) at random order so as to avoid the noise creeping output response. The substrate was preheated to 400°C to relieve the internal stresses and also to reduce the cooling rate to avoid the formation of cracks after deposition [15]. The average Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM 4 S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel Table 4: Macrostructure analysis for fixing the working range of laser hardfacing. S.No Process parameters Parameters range 1 Power (P) 2 3 4 Powder feed rate (F) Travel speed (T) Defocusing distance (D) Macrograph Name of the defect Reason for defect P > 1900 W Crack, dilution Higher heat input P < 1100 W Pores and escaping of powder Insufficient heat input F > 11 g/min Cracks Insufficient specific energy input F < 3 g/min High depth of penetration and dilution Higher specific energy input S > 500 mm/min Cracks Low heat input S < 300 mm/min High dilution Higher heat input D > 37 mm Poor bonding Low energy density per unit D < 17 mm Pores Higher energy density per unit deposited thickness was about 0.8–2 mm of the stainless steel. An automatic disk LH machine was employed to conduct the experiments. Few of the fabricated deposits are displayed in Figure 3. After hardfacing, the deposit was cut into small samples for the metallography and hardness study. A Vickers microhardness testing machine (Make: SHIMADZU, Japan; Model: HMV − 2T) was employed for measuring the hardness across the hardfaced deposit cross section with a load of 0.5 kg and dwell time of 15 s. Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel 5 Table 5: LH process parameters and their working range. S. no Factor 1 2 3 4 Unit Power Powder feed rate Travel speed Defocusing distance Notation W g/min mm/min mm Levels P F T D −2 −1 0 1 2 1100 3 300 17 1300 5 350 22 1500 7 400 27 1700 9 450 32 1900 11 500 37 Figure 2: Single layer hardfacing. Table 6: Design matrix and experimental results. Expt. no. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Coded value P F T D −1 1 −1 1 −1 1 −1 1 −1 1 −1 1 −1 1 −1 1 −2 2 0 0 0 0 0 0 0 0 0 0 0 0 −1 −1 1 1 −1 −1 1 1 −1 −1 1 1 −1 −1 1 1 0 0 −2 2 0 0 0 0 0 0 0 0 0 0 −1 −1 −1 −1 1 1 1 1 −1 −1 −1 −1 1 1 1 1 0 0 0 0 −2 2 0 0 0 0 0 0 0 0 −1 −1 −1 −1 −1 −1 −1 −1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 −2 2 0 0 0 0 0 0 Actual value Hardness of the deposit P F (g/ T (mm/ D (HV) (W) min) min) (mm) 1300 1700 1300 1700 1300 1700 1300 1700 1300 1700 1300 1700 1300 1700 1300 1700 1100 1900 1500 1500 1500 1500 1500 1500 1500 1500 1500 1500 1500 1500 5 5 9 9 5 5 9 9 5 5 9 9 5 5 9 9 7 7 3 11 7 7 7 7 7 7 7 7 7 7 350 350 350 350 450 450 450 450 350 350 350 350 450 450 450 450 400 400 400 400 300 500 400 400 400 400 400 400 400 400 22 22 22 22 22 22 22 22 32 32 32 32 32 32 32 32 27 27 27 27 27 27 17 37 27 27 27 27 27 27 573 475 778 603 475 574 794 703 743 568 820 602 545 581 680 648 727 551 487 770 799 721 575 681 769 766 769 770 766 766 Figure 3: Laser hardfaced deposits. 3 D eveloping an empirical relationship Hardness of deposit is a function of the LH parameters such as power (P), powder feed rate (F), travel speed (T), defocusing distance (D), and it can be expressed as, Hardness of deposit = f (P, F, T, D) (1) Second-order polynomial (regression) equation used to denote the response surface Y is given by, Y = b0 + ∑ bi x i + ∑ bi xi2 + ∑ bijxixj (2) selected polynomial could be expressed as, H = b0 + b1 (P) + b2 (F) + b3 (T) + b4 (D) + b12 (PF) + b13 (PT) + b14 (PD) + b23 (FT) + b24 (FD) + b11 (P ) + b22 (F ) + b33 (T ) (3) + b44 (D2 ) HV 2 2 2 where, b0 is the mean value of response and b1, b2, b3 … b44 are linear interactions and square terms of factors. The value of co-efficient was calculated using Design Expert 7 software at 95% confidence level. The significance of the each co-efficient was calculated from t-test and p-values. The value of “Probe > F” is less than 0.05, indicates that model terms are significant. In this case P, F, T, D, PF, PT, FD, TD, P2, F2 and D2 are the significant terms. The final Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM 6 S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel Table 7: ANOVA test results. Source Model P F T D PF PT PD FT FD TD P2 F2 T2 D2 Residual Lack of fit Pure error Cor total Std. deviation R2 Adj. R2 Sum of squares (SS) 3.334E + 005 41417.04 1.226E + 005 1751.04 7245.38 12265.56 23485.56 1580.06 6201.56 14220.56 10251.56 33380.36 36063.57 2480.86 48696.50 3195.42 2608.08 587.33 3.366E + 005 14.60 0.9905 0.9816 Degree of freedom Mean square F-value p-Value (Prob > F) 14 1 1 1 1 1 1 1 1 1 1 1 1 1 1 15 10 5 29 23817.52 41417.04 1.226E + 005 1751.04 7245.38 12265.56 23485.56 1580.06 6201.56 14220.56 10251.56 33380.36 36063.57 2480.86 48696.50 213.03 260.81 117.47 27.17 47.65 129.73 4.76 8.46 10.09 32.46 1.09 3.00 15.47 11.07 45.15 51.57 1.94 51.89 1.51 Pred. R2 Press Mean CV% Adeq. precision <0.0001 <0.0001 <0.0001 0.0118 <0.0001 <0.0001 <0.0001 0.0157 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0039 <0.0001 0.1959 0.9529 15868.32 671.10 2.17 34.478 Whether significant or not Significant Not significant empirical relationship was built using only these co- expression with the significant terms. The value of adj. efficient and the established final empirical relationship of R2 = 0.981 is also high and indicates the high significance laser hardfaced deposit of Colmonoy-5 alloy is given below. of the model. The pred. R2 value is 0.822 which means that the Hardness of the deposit (H) = [772.50 − 41.92 (P) + 69.17 (F) model could explain 82.2% of the variability in prediction. − 13.25 (T) + 17.67 (D) − 23.62 (PF) + 42.38 (PT) − 7.75 (PD) This is in reasonable agreement with the adj. R2 of 0.952. The value of the coefficient of variation as low as 2.17, + 12.88 (FT) − 29.25 (FD) − 24.75 (TD) − 38.17 (P2 ) which indicates that the deviation between experimental (4) − 40.79 (F2 ) − 7.92 (T2 ) − 40.92 (D2 )] HV and predicted values are low. Adequate measures of the The adequacy of the above relation is tested by analysis of variance (ANOVA). The ANOVA test results are given in Table 7 at the desired confidence level of 95%. The relationship may be considered to be adequate. If the calculated value of the F ratio of the developed relationship does not exceed the tabulated value of F-ratio for an anticipated level of confidence, the model is found to be adequate. The Fisher’s F-test with a very low probability value demonstrates a very high significance of the regression model. The goodness of fit of the model is fitted by the determination coefficient (R2). The coefficient of determination was calculated to be 0.99 in response which implies that 99% of the experimental values confirm the compatibility with data as predicted by the model. The R2 value should always be between 0 and 1. A model is statistically good the R2 value should be close to 1.0. Then adjusted R2 value reconstructs the Figure 4: Correlation graph. Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel 7 Table 8: Confirmation test results for the developed empirical relationship. S. no 01 02 03 Power (W) Powder feed rate (g/min) Travel speed (mm/min) Defocusing distance (mm) Actual hardness (HV) Predicted hardness (HV) Error (%) 1400 1600 1800 4 6 10 325 375 450 20 24 35 585 658 635 570 625 643 −2.6 −5.2 1.2 signal to noise ratio, a ratio greater than 4 is desirable. During this investigation, the ratio is 34.47, which indicates an adequate signal. This model can be used to navigate the design space. The correlation graph shown in the Figure 4, it shows predicted and actual hardness of laser hardfaced deposit, it could indicate the deviation between the actual and predicted hardness is low. Table 8 presents the actual and predicted value of hardness. 4 O ptimizing LH parameters The RSM was used to optimize the LH parameters considered in this study. RSM is a collection of a mathematical and statistical method that are beneficial for designing experiments, constructing a mathematical model, exploratory for the optimal combination of input parameters and pressing out the value in graphically [18, 19]. Figure 5 depicts perturbation plot for the response of hardness of the deposits. This plot offers an outline view of the response and displays the transformation of hardness, when each LH parameter moves from the reference point, with all other parameters held constant as the reference value. The design of experiment sets the reference point by default in the middle of the design space. From the Figure 5: Perturbation graph. perturbation graph and response surface graphs, it can be observed that when the hardness increases with increasing PFR, defocusing distance to the certain level and then decreases. It may be endorsed due to the insufficient energy or low heat input causes the escaping of powders and unmelted partials existing in the deposits. Hardness decreases with increasing laser power, travel speed. It may be believed that the high heat input will increase the depth of penetration and dilution of the deposits [15]. To obtain the influencing nature and optimized condition of the process on hardness (H), the surface and contour plots which are indications of possible independence of factors have been built up for the proposed empirical relation considering two parameters in the halfway tier, and two parameters in the X-axis and Y-axis as shown in Figure 6. The contour plots help us to predict the response at any zone in the design domain [20]. The apex of the response plot shows the maximum achievable hardness. Characterization involves identifying whether the stationary point is a minimum or maximum response or a saddle point to classify this; it is more straightforward to analyze it through a contour plot. Contour plot plays a vital role in the learning the response surface. It is vibrant from that when the hardness increases with increasing PFR, defocusing distance and hardness decrease with increasing laser power, travel speed. To know further about the influencing tendency of process parameters on hardness, three-dimensional diagrams are plotted for a particular processing condition. Figure 6A–F as surface and contour plots for each process parameters. It is clear from Figure 6A that the hardness falls and increases with an increase of process parameters such as laser power and PFR. Hardness mainly depends on dilution and microstructure. Laser power mainly used for melting the powder and excess heat melts the substrate. Keep on increasing the laser power, high volume of substrate material melts. The hardness variation in laser hardfaced sample could affected by the deposit dilution. As higher dilution means lower hardness, increasing P, (constant F, T, D) increases dilution and then hardness decreases. Increasing F (constant P, T, D) diminish dilution so hardness increases because more amount of heat utilized for melting the powder and small amount heat Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM 8 S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel The valley of response plot gives the maximum hardness. These response contours can help in the prediction of the response (hardness) in any zone of the experimental domain [21]. By analyzing the response surface and contour plots as shown in Figure 6A–F, the maximum achievable hardness value is found to be 820.48 HV. The corresponding parameters exist maximum hardness value power of 1314 w, PFR of 9 g/min, a travel speed of 366 mm/min, melt the substrate material. Increasing the T (constant P, F, D), powder density per square area (g/mm2) is less so dilution rate is somewhat increased and hardness is reduced. Increasing the D (constant P, F, T) diminish dilution so hardness increased. When increasing the defocusing distance, the beam size gets larger so the energy density per unit of clad pass available becomes less, thus the penetration depth and dilution decrease. A 677.5 515 352.5 190 11 1900 9 Power feed rate (g/min) Hardness (HV) 840 Powder feed rate (g/min) 507.196 Prediction 820.482 7 667.953 507.196 5 3 1100 1300 3 1100 Power (W) 500 595 447.5 300 Travel speed (mm/min) 1700 350 300 1100 1300 1900 Travel speed (mm/min) 742.5 400 587.575 507.196 426.817 890 450 748.332 5 1500 B 500 426.817 1700 7 Hardness (HV) Hardness (HV) 11 426.817 1300 1500 1700 Power (W) 625.794 1900 722.171 450 625.794 Prediction 820.482 818.549 529.416 350 1500 Power (W) 433.038 300 1100 1300 1500 1700 1900 Power (W) C 403.25 570 440 310 37 1700 32 27 Defocusing distance (mm) 22 17 1100 1300 1900 1500 Power (W) Defocusing distance (mm) 489.799 700 Hardness (HV) Hardness (HV) 37 830 Prediction 820.482 749.445 27 576.348 662.869 22 489.799 17 1100 1300 1500 Power (W) 1700 1900 Figure 6: Response surface graphs and contour plots. (A) Interaction effect of power and powder feed rate. (B) Interaction effect of power and travel speed. (C) Interaction effect of power and defocusing distance. (D) Interaction effect of powder feed rate and travel speed. (E) Interaction effect of powder feed rate and defocusing distance. (F) Interaction effect of travel speed and defocusing distance. Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel 9 D 355.219 697.5 456.578 565 432.5 300 500 450 400 350 Travel speed (mm/min) 7 300 3 9 11 Travel speed (mm/min) Hardness (HV) Hardness (HV) 500 830 450 557.937 760.654 659.295 400 Prediction 820.482 350 5 Powder feed rate (g/min) 300 3 5 7 11 9 Powder feed rate (g/min) E 480 300 120 32 27 Defocusing distance (mm) 22 7 17 3 9 11 Defocusing distance (mm) Hardness (HV) 660 37 Hardness (HV) 37 840 5 Powder feed rate (g/min) 32 Prediction 820.482 722.569 27 600.967 479.364 22 357.762 236.16 17 3 5 7 9 11 Powder feed rate (g/min) F 660 575 490 32 27 Defocusing distance (mm) 22 17 300 350 400 450 500 Defocusing distance (mm) Hardness (HV) 604.983 541.214 668.752 745 37 Hardness (HV) 37 830 732.52 32 Prediction 820.482 796.289 27 22 732.52 Travel speed (mm/min) 668.752 604.983 17 300 350 400 450 500 Travel speed (mm/min) Figure 6 (continued) and defocusing distance of 32 mm at the valley of response surface plot and corresponding domain in the contour plot. Higher F ratio value can give the more significant process parameter. From the F ratio value, it can be concluded that the PFR is contributing the major factor to exploit hardness, followed by power, defocusing distance and travel speed for the range considered in this investigation. To check the prediction capabilities of the developed empirical relationship, three more confirmation tests were carried out with the hardfacing process parameters chosen randomly from the feasible working range (Table 9). The actual response was calculated by taking the average of three results. The developed results reveal that the empirical relationship is accurate since the variation is ±5%. Table 10 summarize the experimental values, predicted values and the variation. Table 11 shows the cross-sectional macrograph, top surface hardness and indentation image of low, medium and high hardness laser hardfaced deposits. Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM 10 S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel Table 9: Validation test results for optimization procedure. S. no 01 02 03 Power (W) Powder feed rate (g/min) Travel speed (mm/min) Defocusing distance (mm) Actual hardness (HV) Predicted hardness (HV) Variation 1386 1414 1329 8.5 9 9 353 437 361 30 25 32 815 809 820 828 821 829 2.7 1.4 1 Table 10: Optimized laser hardfacing parameters. S. no Main parameters 1 2 3 4 5 Power (W) Traverse speed (mm/min) Powder feed rate (g/min) Defocusing distance (mm) Preheating temperature (oC) 1300 350 9 32 400 5 M icrostructure of LH hardfaced deposits LH with powder injection was used to produce multitrack deposits with 50% track overlapping. After the LH, visual inspection of the deposits for both initial compositions revealed a good, continuous appearance without signs of surface cracks or lack of adhesion, as can be seen in the micrograph in Figure 7. Cross sections of the specimens revealed a dendritic structure homogeneously distributed throughout the deposit with a continuous interface, of an unrevealed structure, which corresponds to the dilution zone (Figure 7B). Accordingly, the matrix may be supposed to be composed of a solid solution of Ni-γ with a relatively lower iron and silicon content than the dendrite. Laser-deposited layers in general, three different microstructures from the bottom to top: a plane solidification front microstructure with limited thickness, a transition cellular microstructure, and a columnar-dendritic microstructure. In addition to that, Table 11: Cross-sectional macrograph and top surface hardness indentation of laser hardfaced deposit. Deposit no LH parameters 01 P – 1300 W F – 5 g/min T – 350 mm/min D – 22 mm 04 P – 1700 W F – 9 g/min T – 350 mm/min D – 22 mm 11 P – 1300 W F – 9 g/min T – 350 mm/min D – 32 mm Macrograph Hardness with indentation Hardness (HV0.5) 475 603 820 Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel 11 Figure 7: Various microstructures of hardfaced deposits observed by OM. (A) Low magnification cross-section. (B) Hardfaced deposit-interface. (C) Hardfaced deposit-middle. (D) Hardfaced deposit-top surface. (E) HAZ. (F) Substrate. (G) Precipitates at top of the deposit. (H) Precipitates at near the interface. Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM 12 S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel Figure 8: EDS line scan of the constituent elements across substrate/deposit interface (optimized condition). the evolution of fourth region which consists of equiaxed grains at the top (Figure 7D). The microstructure at each region depends on the cooling rate and temperature gradient. In the laser-deposited Ni-based layer, the main solidification structure is characterized by columnar crystals at the bottom and equiaxed crystals on the top surface. Due to the high-temperature gradient (G), and lower solidification rate (V), at the solid-liquid interface, epitaxial growth from the substrate occurs in the bottom area, showing a typical directional solidification characteristic. In the top area of the melt pool, columnar crystals disappear and equiaxed crystals appeared due to the local lower G and higher V conditions [22]. The interface appears well defined with a zone that is apparently free of precipitates (Figure 7E). However, at greater magnification the existence of a new arborescent phase, whose composition is the same as the dendrites indicating an epitaxial growth. In the overlapped tracks, higher concentrations of dark precipitates are observed. This may be due to the remelting of the former track during LH. This remelting will produce higher segregation of eutectics at the interface between overlapping tracks. The existence of these eutectics is mainly depending on Cr and C concentrations at the particular region. Laser deposited Colmonoy 5 coatings consists of three general components: Cr-rich precipitates such as CrB, CrC, Ni solid solution dendrites, Ni-B-Si binary and ternary eutectic phases including NiB, NiSi (Figure 7G and H) [23]. Figure 8 shows the line scan EDS it gathers the values of each element (wt.%) as a function of the distance from the substrate, interface and deposit. As can be seen, substrate consist of iron content is around 70–75%. Near the interface iron content drastically reduced it is conformed that dilution is very low, iron content passing from 80% at the interface to 4% in the deposit. The dilution ensures a perfect bond between the metal and the clad layer, and on the other hand the low level of dilution confirms the quality of the coating that’s improve the hardness of the deposit. The silicon content is around 4%, the chromium content around 8% and the nickel content between Figure 9: Scanning electron micrograph of the deposit and spot EDS (optimized condition). Brought to you by | National University of Singapore - NUS Libraries Authenticated Download Date | 10/28/17 1:22 PM S. Gnanasekaran et al.: Optimizing the laser parameters to attain maximum hardness in nickel 13 80 and 85% in the deposit. EDS spectra shows that the precipitates in the cluster (spot 1) are rich in Cr with fewer additions of C, Si, Ni and Fe as showed in Figure 9. The second spot EDS are rich in Ni with definite counts of Cr, Fe and Si as showed in Figure 9 (spot 2). In addition, the EDS spectra reveal the eutectic interdendritic constituent containing particles of Ni-rich compounds, preferably Ni-borides. 6 Conclusions 1. An empirical relationship was developed to predict the hardness of nickel-based layer deposited on 316LN austenitic stainless-steel substrate with 95% confidence level by incorporating important LH parameters. 2. A maximum hardness of 829.44 HV could be achieved in the deposit made using laser power of 1314 W, PFR of 9 g/min, a travel speed of 366 mm/min, and defocusing distance of 32 mm. 3. Of the four LH parameters, the PFR (based on F value) is the major influencing factor to predict the hardness followed by power, travel speed and defocusing distance. Acknowledgments: The authors are thankful to UGC-DAE consortium for providing financial assistance to carry out this investigation (Project No. CSR-KN/CRS-56/2013-14/656 dated 04.09.13). Authors wish to express their sincere thanks to M/s. Geometrix Laser Solutions Pvt Limited, Tada for laser hardfacing facility. Authors also express their sincere thanks to The Director, IGCAR, Kalpakkam for the base metal supply. References [1] Atamert S, Bhadeshia HKDH. Metall. Trans. A 1989, 20, 1037–1054. [2] Frenk A, Kurz W. Mater. Sci. Eng. A 1993, 173, 339–342. [3] Tiziani A, Giordano L, Matteazzi P, Badan B. Mater Sci. Eng. 1987, 88, 171–175. [4] Arif AFM, Yilbas BS. J. Mater. Eng. Perform. 2008, 17, 644–650. [5] Liu Z, Cabrero J, Niang S, Al-Taha ZY. Surf. Coat. Technol. 2007, 201, 7149–7158. [6] Navas C, Vijande R, Cuetos JM, Fernández MR, de Damborenea J. Surf. Coat. Technol. 2006, 201, 776–785. [7] Schmidt RD, Ferriss DP. Wear 1975, 32, 279–289. [8] Davis JR. 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