Optimization of the process parameters in generic thermal barrier coatings using the Taguchi method and grey relational analysis

Kumar, Dhirendra; Pandey, Kavita

doi:10.1177/1464420715602727

Cited by 11 publications

(9 citation statements)

References 31 publications

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“…Top-coat was prepared by the APS using optimized process parameters. 61 The purpose was to assess its applicability in hot-zone components of internal combustion engine such as piston, combustion chamber, cylinder part, and exhaust valve. Following are the conclusions of the present work: The XRD result shows highly stabilized tetragonal phase.…”

Section: Discussionmentioning

confidence: 99%

“…The top-coat of 7YSZ on the already deposited bond-coat was made on the basis of optimized process parameters of APS obtained by Taguchi and grey relation analysis (GRA) to get good quality of top-coat. 61 The optimized process parameters of APS for top-coat are given in Table 3. The material for top-coat was 7YSZ (by wt%) commercial powder (chemical composition as per AMPERIT No.…”

Section: Materials and Proceduresmentioning

confidence: 99%

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Characterization of air plasma based 7YSZ aluminum alloys thermal barrier systems for hot zone

Kumar

Pandey

Das

2016

Proceedings of the Institution of Mechanical Engineers, Part L:

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Characterization of yttria-stabilized zirconia coatings deposited on AA2024-T351 aluminum alloy by air plasma spraying is carried out in the present work to assess its applicability as a thermal barrier coating on automotive components aluminum alloys. Tetragonality of coating microstructures was confirmed through X-ray diffractometer, transmission electron microscopy, and high-resolution transmission electron microscopy. Lattice-image spacing obtained from highresolution transmission electron microscopy confirmed multilayer structure of the coating and that the tetragonal phases are stable. From the optical microscopy it was found that there are good coating particle distribution and homogeneity of coating particles on the substrate while atomic force microscopy provided information about surface bumps and pits. Small roughness of the coating microstructure was found to be very low. Small roughness showed good deposition efficiency of the coating structures.

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Section: Discussionmentioning

confidence: 99%

Section: Materials and Proceduresmentioning

confidence: 99%

Characterization of air plasma based 7YSZ aluminum alloys thermal barrier systems for hot zone

Kumar

Pandey

Das

2016

Proceedings of the Institution of Mechanical Engineers, Part L:

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“…The data analysis method could be applied to optimize the combination of the blasting parameters. For example, the Taguchi design method is the most generally employed data analysis method to evaluate the influence rank of various preprocessing parameters on the coating's performance qualitatively [21,22]; the multiple linear regression method is commonly applied to establish the quantitative relationship among the grit blasting process parameters, the substrate surface condition and coating performance [23]. Nevertheless, these traditional analysis and modeling methods cannot meet the higher requirements of the actual grit blasting guidance.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Analysis of the Grit Blasting Process on the Corrosion Resistance of Thermal Spray Coatings Using a Hybrid Artificial Neural Network

Pan

et al. 2021

Coatings

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Grit blasting as a pretreatment process for the substrate surface before thermal spraying is of great importance for assuring the service performance of thermal spraying coatings. In this work, a novel hybrid artificial neural network (ANN) was presented to optimize the grit blasting process to improve the structural properties and corrosion resistance performance of thermal spraying coatings. Different grit blasting process parameters were combined to pretreat the substrate surface, and the corresponding surface roughness, interface adhesion strength and corrosion resistance performance were obtained. Hence, a backpropagation (BP) neural network model optimized by the genetic algorithm (GA) was presented to address the poor regression roughness and accuracy of the traditional fitting models; the grit blasting processing parameters were utilized as the inputs for the GA–BP model; the structural properties and the corrosion resistance performance were used as the outputs. The correlation coefficient R reached and exceeded 0.90, and three error values were less than 1.75 on the prediction of the service performance of random samples. All these indicators demonstrated convincingly that the obtained hybrid artificial neural network models possessed good prediction performance, and this innovative and time-saving grit blasting process optimization approach could be potentially employed to improve the comprehensive service performance of thermal spraying coatings.

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“…The Taguchi approach is normally suitable for the optimization of a single objective. To solve the multi-objective optimization of thermal spray processes, several authors have developed the Taguchi-OEC technique, 9 Taguchi-based gray relational analysis 10,11 and response surface methodology. 12,13 Pal and Gauri 14 introduced the multiple regression-based weighted signal-to-noise ratio (MRWSN) optimization method, which was based on a combination of the Taguchi and mathematical regression techniques.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of WC-12Co coating by high-velocity oxygen fuel spray using multiple regression-based weighted signal-to-noise ratio

Nguyen

Doan

Tong

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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In this study, the optimal process parameters for a high-velocity oxygen fuel spray, which was used to deposit WC-12Co coating on a 16Mn steel substrate, were studied to simultaneously improve the microhardness, adhesion strength, and porosity of the coating. To this end, trial tests were conducted to determine the feasible ranges of the spray parameters: powder feed rate ( A), spray distance ( B), and oxygen/propane mixture ratio ( C). Taguchi orthogonal array (L9) experimental design was used to determine regression formulae for the microhardness, adhesion strength, and porosity. Then, based on a method using the multiple regression-based weighted signal-to-noise ratio, the optimal spray parameters were identified. To verify the optimization results, confirmation experiments were carried out. An analysis of variance was also conducted to check the proportion of contribution of the spray parameters on the output quality characteristics. The confirmation test results proved that the predicted and measured results were in good agreement. The optimal conditions of the high-velocity oxygen fuel spray were: A = 32 g/min, B = 0.35 m, and C = 5. The estimated optimal coating properties were: microhardness = 1335.784 HV, adhesion strength = 64.659 MPa, and porosity = 1.797%. The oxygen/propane ratio showed the highest contribution to the microhardness, whereas the most influential factor for both adhesion strength and porosity was the spraying distance.

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Optimization of the process parameters in generic thermal barrier coatings using the Taguchi method and grey relational analysis

Cited by 11 publications

References 31 publications

Characterization of air plasma based 7YSZ aluminum alloys thermal barrier systems for hot zone

Characterization of air plasma based 7YSZ aluminum alloys thermal barrier systems for hot zone

Prediction and Analysis of the Grit Blasting Process on the Corrosion Resistance of Thermal Spray Coatings Using a Hybrid Artificial Neural Network

Multi-objective optimization of WC-12Co coating by high-velocity oxygen fuel spray using multiple regression-based weighted signal-to-noise ratio

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