Using response surface methodology for optimizing deposited partially stabilized zirconia in plasma spraying
Introduction
Thermal barrier coating is a relatively new technique that has come into use in the last two decades. It is used in several activities aimed at gas turbine engines with specific coating of superalloy materials to improve their efficiency. It also provides thermal resistance to the metallic substrate and reduces the substrate surface temperatures in many power generation systems, and hence improves the durability of the components in these systems. Instead of developing new bulk thermal resistance materials, thermal barrier coating is now the current trend for solving the engines’ thermal problems [1], [2]. It is ideal to find a specified superalloy coating on substrate matrix not only with low costs, but also with a good performance for high precision materials that are extremely difficult using conventional treatment processes. The plasma spray coating is a popular and efficient method of forming thermal barrier coatings. Compared to other ceramics, zirconia-based materials are preferred as coating materials in engineering applications due to its superior mechanical properties, such as anti-heat, low thermal conductivity, large coefficient of thermal expansion and stability, as well as good wear resistance.
Among the various coating materials of partially stabilized zirconia (PSZ), several binary and ternary oxide systems have also been developed as potential sources of hardening zirconia polycrystals. The application of zirconia-base with various stabilizing oxides such as MgO, CaO, CeO and Y2O3 is quite well known in thermal barrier coating that is made mostly by plasma spray. However, partially stabilized zirconia coating provides the most desirable properties in the anti-heat of these coatings and, therefore, is widely used. Zirconia-based coating after thermal barrier treatments has been the subject of numerous investigations. Studies focused on the identification and quantification of phase transformations in plasma spray coatings have been done [3], [4], [5]. These characteristics are helpful in predicting the coating behavior under controllable plasma spray processes, but are not sufficient in finding the means of a systematically optimal coating. In thermal barrier coating processes, appropriate modeling of a process model is hardly efficiently used, nor is a systematic analysis of the relationship between independent variables and responses. Further, the impacts and importance of plasma spraying process factors on the surface coatings are still not well understood. Therefore, it is desirable to develop a systematic design in the plasma spraying process.
Due to the nature of the surface hardening process and the noise variation, it is typical and reasonable to present process characteristics with a nonlinear model. In this paper, we applied the response surface methodology (RSM) that helps in developing a suitable approximation for the true functional relationship between the independent variables and the response variable that may characterize the nature of the coatings [7], [8], [9], [12]. This paper illustrates the two-stage optimal procedures. In the first-stage, the analysis of variance (ANOVA) is efficiently utilized for selecting the most significant factors among numerous factors that are to be further analyzed in a response surface model. In the second-stage, a RSM model is obtained from the statistical fitting method. Including only the important factors, the RSM model could efficiently present an approximate functional relationship from the experimental data. A second-order RSM model is used to generate the response surfaces under various conditions. This study also demonstrates the procedure of applying statistical technologies to optimize plasma spray coating for effective productions.
Section snippets
Plasma spraying
Thermal spraying is the process of spraying molten metal onto a surface to form a coating. Pure or alloyed metal is melted in a flame or electric arc and atomized by a blast of compressed air. The resulting fine spray builds upon a prepared surface to form a solid metal coating. Plasma spraying is a thermal spraying process in which a nontransferred arc of the gun is used to create an arc plasma for melting and propelling the surfacing material to the substrate. It is this process of applying a
The experimental design
Several experimental studies on the effects of two or more factors have been conducted [6]. It can be shown that factorial designs are usually most efficient for this type of experiment. A complete factorial design requires experiments including all possible combinations of the levels of the factors, which can be very expensive and time-comsuming. Therefore, fractional factorial designs can be used as an efficient alternative. A fractional factorial design requires running only a fraction of
Deposited micrographs
For the illustration purpose, Fig. 2 shows the magnified surface coating morphologies of the PSZ reinforced substrate coatings spray for Tests 6, 15 and 16 in Table 3. It can be seen that some partially melted and unmelted small particles are formed in the partially stabilized zirconia coatings because feedstock materials are heated and propelled as individual particles or droplets onto a surface [13]. Fig. 3 shows three typical cross-sectional SEM photographs of the plasma spray coatings
Concluding remarks
It was experimentally shown that the use of fractional factorial experiments coupled with statistical fitting model strategy is a simple, effective and efficient way to approach for developing robust, highly efficient, high quality plasma spray coating process. Optimization of processing variables and responses in the plasma spray coating process has been achieved through appropriate construction of the process model in RSM. Based on the experimental results, the following conclusions have been
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