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Optimization of the Burnishing Process for Energy Responses and Surface Properties

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Abstract

In the current work, the optimal factors are selected to achieve the improvements in the energy consumption (EB), power factor (PB), decreased roughness (DR) and improved surface hardness (IH) for the roller burnishing operation. The process inputs are the burnishing speed (V), the feed (f), and the depth (d). A hybrid approach comprising the principal component analysis and Technique for Order of Preference by Similarity to Ideal Solution was used to explore the weight values of burnishing performances and select the optimum parameters. Moreover, another optimization technique employing the response surface method and archive-based micro-genetic algorithm was adopted to identify the optimal outcomes in the continuous domain. The main findings showed the performances measured are primarily affected by the burnishing feed, depth and speed, respectively. The energy consumption and roughness are approximately decreased by 31.46% and 7.41%, while the power factor and hardness are improved by 17.47% and 43.09%, respectively, as compared to the general process. The outcomes and findings of the investigated work can be used for further research in sustainable design and manufacturing as well as directly used in the knowledge-based and expert systems for burnishing applications in industrial practices.

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References

  1. El-Taweel, T. A., & El-Axir, M. H. (2009). Analysis and optimization of the ball burnishing process through the Taguchi technique. The International Journal of Advanced Manufacturing Technology,41, 301–310.

    Article  Google Scholar 

  2. John, R. S., & Vinayagam, B. K. (2011). Optimization of ball burnishing process on tool steel (T215Cr12) in CNC machining centre using response surface methodology. Arabian Journal for Science and Engineering,36, 1407–1422.

    Article  Google Scholar 

  3. Babu, P. R., Ankamma, K., Prasad, T. S., Raju, A. V. S., & Eswara Prasad, N. (2012). Optimization of burnishing parameters and determination of select surface characteristics in engineering materials. Sadhana,37, 503–520.

    Article  Google Scholar 

  4. Tadic, B., Todorovic, P. M., Luzanin, O., Miljanic, D., Jeremic, B. M., & Bogdanovic, B., et al. (2013). Using specially designed high-stiffness burnishing tool to achieve high-quality surface finish. The International Journal of Advanced Manufacturing Technology,67, 601–611.

    Article  Google Scholar 

  5. John, M. R. S., & Vinayagam, B. K. (2014). Optimization of nonlinear characteristics of ball burnishing process using Sugeno fuzzy neural system. The Journal of the Brazilian Society of Mechanical Sciences and Engineering,36, 101–109.

    Article  Google Scholar 

  6. Revankar, G. D., Shetty, R., Rao, S. S., & Gaitonde, V. N. (2014). Analysis of surface roughness and hardness in ball burnishing of titanium alloy. Measurement,58, 256–268.

    Article  Google Scholar 

  7. Cobanoglu, T., & Ozturk, S. (2015). Effect of burnishing parameters on the surface quality and hardness. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering,229(2), 286–294.

    Article  Google Scholar 

  8. Banh, Q. N., & Shiou, F. J. (2016). Determination of optimal small ball-burnishing parameters for both surface roughness and superficial hardness improvement of STAVAX. Arabian Journal for Science and Engineering,41(2), 639–652.

    Article  Google Scholar 

  9. Yuan, X. L., Sun, Y. W., Gao, L. S., & Jiang, S. L. (2016). Effect of roller burnishing process parameters on the surface roughness and microhardness for TA2 alloy. The International Journal of Advanced Manufacturing Technology,85, 1373–1383.

    Article  Google Scholar 

  10. Amdouni, H., Bouzaiene, H., Montagne, A., Nasri, M., & Iost, A. (2017). Modeling and optimization of a ball-burnished aluminum alloy flat surface with a crossed strategy based on response surface methodology. The International Journal of Advanced Manufacturing Technology,88, 801–814.

    Article  Google Scholar 

  11. Teimouri, R., Amini, S., & Bami, A. B. (2018). Evaluation of optimized surface properties and residual stress in ultrasonic assisted ball burnishing of AA6061-T6. Measurement,116, 129–139.

    Article  Google Scholar 

  12. Nguyen, T. T., & Le, X. B. (2018). Optimization of interior roller burnishing process for improving surface quality. Materials and Manufacturing Processes,33(11), 1233–1241.

    Article  Google Scholar 

  13. Nguyen, T. T., & Le, X. B. (2019). Optimization of roller burnishing process using Kriging model to improve surface properties. Proceedings of the Institution of Mechanical Engineers, Part B,233(12), 2264–2282.

    Article  Google Scholar 

  14. Chinnaiyan, P., & Jeevanantham, A. K. (2014). Multi-objective optimization of single point incremental sheet forming of AA5052 using Taguchi based grey relational analysis coupled with principal component analysis. International Journal of Precision Engineering and Manufacturing,15, 2309–2316.

    Article  Google Scholar 

  15. Soepangkat, B. O. P., Pramujati, B., & Effendi, M. K., et al. (2019). Multi-objective optimization in drilling kevlar fiber reinforced polymer using grey fuzzy analysis and backpropagation neural network-genetic algorithm (BPNN–GA) approaches. International Journal of Precision Engineering and Manufacturing,20, 593–607.

    Article  Google Scholar 

  16. Zhang, F. Y., Chen, J. L., & Li, T. T., et al. (2019). Study and optimization of structural parameters of oil seal by response surface method. International Journal of Precision Engineering and Manufacturing,20, 255–265.

    Article  Google Scholar 

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Acknowledgements

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under Grant Number 107.04-2020.02.

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Authors and Affiliations

  1. Institute of Research and Development, Duy Tan University, 03 Quang Trung, Da Nang, 550000, Vietnam

    Trung-Thanh Nguyen

  2. Faculty of Mechanical Engineering, Le Quy Don Technical University, 236 Hoang Quoc Viet, Ha Noi, 100000, Vietnam

    Trung-Thanh Nguyen & Le-Hai Cao

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  1. Trung-Thanh Nguyen
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  2. Le-Hai Cao
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Correspondence to Trung-Thanh Nguyen.

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Nguyen, TT., Cao, LH. Optimization of the Burnishing Process for Energy Responses and Surface Properties. Int. J. Precis. Eng. Manuf. 21, 1143–1152 (2020). https://doi.org/10.1007/s12541-020-00326-8

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  • DOI: https://doi.org/10.1007/s12541-020-00326-8

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