OPTIMIZATION OF BIOCOMPATIBLE MATERIALS DEPOSITED BY HVOF THERMAL SPRAYING PROCESS

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1 OPTIMIZATION OF BIOCOMPATIBLE MATERIALS DEPOSITED BY HVOF THERMAL SPRAYING PROCESS Ibolyka BRAN a, Radu Alexandru ROŞU a, Mihaela POPESCU a, Carmen OPRIŞ a, Ion GROZAV a Politehnica University of Timişoara, Faculty of Mechanical Engineering, Bd. Mihai Viteazu Nr.1, Timişoara, Romania, address: ibi.bran@gmail.com Abstract Thermal spraying is a process with an increasing applicability, which involves technology development, equipment, exhaust ventilation systems, all under the aegis of the concerns of the International Institute of Welding (IIW / IIW), Commission IC and VIII, Occupational Safety and Health Administration (OSHA) and European Welding Federation (EWF) for improving staff working in the field. The interdisciplinary field of thermal spraying (HVOF process) with the participation of knowledge of metallurgy, including also powder metallurgy, chemical, surface engineering, technology, automation, control, are described in the paper. The applicability of HVOF thermal spraying deposition to achieve biocompatible orthopedic and dental implants of hydroxyapatite type required an optimization of technological parameters of HVOF thermal spray process. The MINITAB 14 program was used for Design of Experiments (DOE) which was carried out with exceptional results for similar structures for human bone, which thus facilitates rapid restoration of tissue-implant bond. Note that metallic biocompatible materials are used in medical implants because they possess good mechanical properties. To improve the adherence of the implant it is deposited on the surface of the metallic implants ceramic materials with biocompatible and bioactive properties. Hydroxyapatite is such a material used due to its mineral composition which is similar to human bone tissue, thus justifying the research and studies developed. Keywords: thermal spraying, HVOF, biocompatibility, design of experiments (DOE), hydroxyapatite 1. INTRODUCTION Thermal spraying is a process connected to welding, with applicability in various domains. If initially thermal spraying was applied only for surface protection, it later extended its practicability for rapid prototyping, for ensuring hard facing; one of the latest domains is represented by the deposition of biocompatible materials for implants and human prosthesis. HVOF (High Velocity Oxy-Fuel) stands out from the multitude of variants of thermal spraying due to the low temperature developed during spraying. The structure of the powder used for the coating suffers minor modifications compared to other thermal spraying processes. 1.1 HVOF Thermal spraying method principle HVOF (High Velocity Oxy-Fuel) is a modern thermal spraying method which has the particularity that it produces very high speeds of the jet. Gas stream reaching temperatures up to 2800 C and speeds of 2500 m/s accelerates and plastify the particles of the powder to be deposited up to 800 m/s and than projects it on the substrate [1]. The schematic principle of HVOF thermal spraying gun is shown in figure 1. Hydroxyapatite is a calcium phosphate ceramic material which is used with good results in medicine to cover dental and orthopaedic implants due of its biocompatible and bioactive properties [5-8].

2 Fig. 1. Principle of HVOF thermal spraying gun [2] Hydroxyapatite s structure is similar to that of the human bone mineral component, behaving as a reservoir of elements which help the fixation of the implant in the bone tissue. Because hydroxyapatite has low mechanical properties, it can be used for medical implants, but only to cover them. The metallic implants can be covered with hydroxyapatite layers by various processes: plasma thermal spraying, laser beam, high velocity oxy-fuel (HVOF), sol-gel. [3-8]. 2. EXPERIMENTAL PROCEDURE HVOF thermal spraying process is influenced by a large number of parameters. These parameters, influencing the properties of hydroxyapatite coatings, will be selected and analyzed with the Minitab 14 computer program. This software helps us to design the experiments, for finding the most influents parameters (control factors) and also to make a first mathematical model of the process (a linear one). Using this linear model is also possible to make a first optimization of the process. The following parameters are considered important and will be analyzed during this experiment: oxygen, hydrogen, kerosene and nitrogen (carrier gas) flow. All these parameters are easily controllable and may be adjusted. Table 1 shows the parameters and the variation domain that will be investigated during the experiments. Table 1 Parameters to be investigated with the Minitab 14 program Parameter Minim Maxim Oxygen flow (l/min) Hydrogen flow (l/min) Kerosene, (l/h) 2,8 3 Carrier gas (nitrogen), (l/min) Using these input data, the Minitab 14 computer program has generated an experimental program presented in table 2.

3 Table 2 Experimental data generated by the Minitab 14 program StdOrder RunOrder CenterPt Blocks O 2 H K Gas Roughness Thickness ,8 15 5, ,8 15 5, ,8 15 5, StdOrder RunOrder CenterPt Blocks O 2 H K Gas Roughness Thickness , , ,8 20 5, , , , ,8 20 5, ,8 20 5, ,8 15 5, , , ,8 20 5, , The influence of the HVOF process parameters on the roughness and thickness of the hydroxyapatite coatings has been analyzed in this experiment, as follows. Factorial Fit: Roughness; Thickness Factorial Fit: Roughness versus O2; H; K; Gas Estimated Effects and Coefficients for Roughness (coded units) Term Effect Coef SE Coef T P Constant 5,4063 0, ,74 0,000 O2-0,1925-0,0962 0, ,45 0,040 H -0,0525-0,0262 0, ,67 0,522 K -0,0725-0,0363 0, ,92 0,383 Gas -0,0425-0,0212 0, ,54 0,603 O2*H -0,0875-0,0438 0, ,11 0,297 O2*K -0,0775-0,0388 0, ,99 0,352 O2*Gas -0,2275-0,1138 0, ,90 0,020 S = 0, R-Sq = 69,49% R-Sq(adj) = 42,80% Significant influence have O 2 and second order interaction O 2 *Gas, since they have p<0,05. Analysis of Variance for Roughness (coded units) Source DF Seq SS Adj SS Adj MS F P Main Effects 4 0,1875 0,1875 0, ,90 0,204 2-Way Interactions 3 0,2617 0,2617 0, ,54 0,068 Residual Error 8 0,1972 0,1972 0,02465 Pure Error 8 0,1972 0,1972 0,02465 Total 15 0,6464

4 Term Term , Brno, Czech Republic, EU AD A Pareto Chart of the Standardized Effects (response is Rugozitate, Alpha =,05) 2,306 F actor Name A O2 B H C K D Gaz AD A Pareto Chart of the Standardized Effects (response is Grosime, Alpha =,05) 2,306 F actor Name A O2 B H C K D Gaz AB D AC AB C AC B D C B 0,0 0,5 1,0 1,5 2,0 Standardized Effect 2,5 3, Standardized Effect 3 4 Fig. 2. Effects Pareto for Roughness Fig. 3. Effects Pareto for Thickness The Pareto chart for Roughness, presented in fig. 2 emphasizes the significant effects previously presented. For Thickness, the Pareto chart from fig. 3 emphasizes the significant influence of second order interaction O 2 *Gas. The presence of the second order interaction with significant effect signifies one must be careful with the conclusions. Factorial Fit: Thickness versus O2; H; K; Gas Estimated Effects and Coefficients for Thickness (coded units) Term Effect Coef SE Coef T P Constant 189,688 1, ,51 0,000 O2-7,375-3,688 1,764-2,09 0,070 H -2,125-1,062 1,764-0,60 0,564 K -2,625-1,313 1,764-0,74 0,478 Gas -4,875-2,437 1,764-1,38 0,204 O2*H -3,875-1,937 1,764-1,10 0,304 O2*K -3,375-1,688 1,764-0,96 0,367 O2*Gas -13,125-6,562 1,764-3,72 0,006 S = 7,05780 R-Sq = 74,31% R-Sq(adj) = 51,84% For thickness a significant influence has the second order interaction O 2 *Gas and it can be seen that O 2 is close to significant influence. Analysis of Variance for Thickness (coded units) Source DF Seq SS Adj SS Adj MS F P Main Effects 4 358,3 358,3 89,56 1,80 0,223 2-Way Interactions 3 794,7 794,7 264,90 5,32 0,026 Residual Error 8 398,5 398,5 49,81 Pure Error 8 398,5 398,5 49,81 Total ,4 Second order interaction have a significant influence (p<0,05). The software MINITAB gives the possibility to draw the contour plots for all investigated parameters. These are presented in figure 4. The contour plots for roughness (see fig. 4 a) show that for having high values for roughness we have to use high values for O 2, H and low values for K. For Gas the desired values for roughness can be reached for low, respectively for high values of this parameter. O similar tendency can be seen for the case of thickness, as presented in figure 4 b.

5 For all researcher is important to find an optimal solution, that gives the best solution for assuring the desired values of the responses of the process, in our case a maximum value for roughness and a desired value for thickness, respectively thickness = 180 microns. a) b) Fig. 4 Contour plots for Roughness (a) and Thickness (b) MINITAB offers the possibility to optimize the process. The desired targets and the global solution of this optimization are: Response Optimization Parameters Goal Lower Target Upper Weight Import Roughness Maximum 5 5,4 5,4 1 1 Thickness Target ,0 190,0 1 1 Global Solution O2 = 320,000 H = 92,488 K = 2,800 Gas = 20,000 Predicted Responses Roughness = 5,250; desirability = 0,62587 Thickness = 180,015; desirability = 0,99850 Composite Desirability = 0,79053

6 A graphical representation of the optimal solution and the optimal values of the parameters are presented in table 3. Table 3 Parameters after process optimization Process optimization ensured the desired values in a global proportion of 79%, and for each process response, the values are presented in table CONCLUSIONS Roughness and thickness are two important parameters of the coatings obtained by thermal spraying, especially in the case of hydroxyapatite. Roughness especially is important in the case of implants coated with hydroxyapatite, since osteoblast cell attachment is improved on a rough surface. Coating thickness also plays a key role on the implant s properties because a thicker hydroxyapatite layer protects the bone from metallic ions released by the implant s metallic structure. The MINITAB 14 program was used for Design of Experiments (DOE) which was carried out with exceptional results for similar structures for human bone, which thus facilitates rapid restoration of tissue-implant bond. Using this statistical software it was possible to find the optimal parameters values for having the desired values of the process responses. Acknowledgement This work was partially supported by the strategic grant POSDRU/89/1.5/S/57649, Project ID (PERFORM-ERA), co-financed by the European Social Fund Investing in People, within the Sectoral Operational Programme Human Resources Development REFERENCES [1.] MINGHENG, Li., PANAGIOTIS, D., 2006 Computational study of particle in-flight behavior in the HVOF thermal spray process. Chemical Engineering Science, Vol. 61, s ISSN [2.] SHAHRIAR, H., Design of Experiment Analysis of High Velocity Oxy-Fuel Coating of Hydroxyapatite, PhD Thesis, School of Mechanical and Manufacturing Engineering, Dublin City University, Ireland, 2009, 124 p. [3.] LEVINGSTONE, T.J., Ceramics for Medical Applications, Dublin City University, Ireland. [4.] SHI, D., Introduction to Biomaterials, World Scientific, Tsinghua University Press, China, 2008, ISSN , 200 p. [5.] PARK, E., CONDRATE Sr. Characterization of hydroxyapatite: Before and after plasma spraying. Journal of Material Science: Materials in Medicine, 2002, Vol. 13, page , ISSN: [6.] ROY, R., Design of Experiments using the Taguchi Approach: 16 Steps to Product and Process Improvement, John Wiley & Sons Ltd., New York, ISBN [7.] STOKES, J., 2008, The Theory and Application of the Sulzer Metco HVOF (High Velocity Oxy-Fuel) Thermal Spray Process, Dublin City University, Ireland, ISBN

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