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Back propagation model for prediction of deposition parameters in plasma sprayed WC-based coatings

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Abstract

The deposition parameters frequently have a significant impact on the characteristics of plasma spray coating. Due to the intricate chemical and thermodynamics processes, it is challenging to study and create a complete model of plasma spray process. The use of WC-based coatings, which offers exceptional wear resistance, in turbomachinery components such as blades, vanes, extend their service life and lowers need of maintenance. The objective of this investigation is to develop a predictive model for mechanical properties of plasma deposited WC20Cr3C27Ni coatings using a back propagation neural network. Additionally, the study also analyses the impact of deposition parameters irrespective of the intermediate process. The change in porosity, nano-hardness, and sliding wear rate of coatings under various powder feed rate, stand-off distance, and powder gas N2 flow rate was predicted using back propagation neural network algorithm. The developed model accurately predicted the characteristics of WC-based coatings, evidenced by a comparison between predicted and experimental results that shows similar trends. In order to specifically evaluate each input variable’s relative importance for improving prediction accuracy, the mean impact value analysis was used.

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The authors also declare that the data is available on the request.

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Acknowledgements

The authors wish to thank Metallizing Equipment Pvt. Ltd., Jodhpur, India, for providing the coating facility. The authors are grateful to IIT Bombay, India, for providing the testing facilities such as SEM and nano-indentation. This research work did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Artificial Intelligence and Data Science, Dr. D. Y. Patil Institute of Technology, Pune, Maharashtra, 411 018, India

    Shubhangi Suryawanshi

  2. Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Pune, Maharashtra, 411 018, India

    Digvijay G. Bhosale

  3. School of Mechanical Engineering, Lovely Professional University, Phagwara, 144 411, India

    Hitesh Vasudev

  4. CEMILAC, Defence R and D Organization, DRDO, Bangalore, Karnataka, 560 093, India

    T. Ram Prabhu

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  1. Shubhangi Suryawanshi
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Correspondence to Shubhangi Suryawanshi.

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Suryawanshi, S., Bhosale, D.G., Vasudev, H. et al. Back propagation model for prediction of deposition parameters in plasma sprayed WC-based coatings. Int J Interact Des Manuf (2024). https://doi.org/10.1007/s12008-024-01863-6

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