OBRABOTKAMETALLOV Vol. 24 No. 3 2022 52 TECHNOLOGY 4. Sahin Y. Analysis of abrasive wear behavior of PTFE composite using Taughi’s technique. Cogent Engineering, 2015, vol. 2, no. 1, pp. 1–15. DOI: 10.1080/23311916.2014.1000510. 5. Venkateswarlu G., Sharada R., Rao M.B. Effect of fi llers on mechanical properties of PTFE based composites. Archives of Applied Science Research, 2015, vol. 7, no. 7, pp. 48–58. 6. Wang Q., Zhang X., Pei X. Study on the synergistic effect of carbon fi ber and graphite and nanoparticle on the friction and wear behavior of polyimide composites. Materials and Design, 2010, vol. 31, no. 8, pp. 3761–3768. DOI: 10.1016/j.matdes.2010.03.017. 7. Song F., Wang Q., Wang T. Effect of glass fi ber and MoS2 on tribological behaviour and PV limit of chopped carbon fi ber reinforced PTFE composite. Tribology International, 2016, vol. 104, pp. 392–401. DOI: 10.1016/j.triboint.2016.01.015. 8. Gujrathi S.M., Dhamande L.S., Patare P.M. Wear studies on polytetrafl uroethylene (PTFE) composites: Taguchi approach. Bonfring International Journal of Industrial Engineering and Management Science, 2013, vol. 3, no. 2, pp. 47–51. DOI: 10.9756/BIJIEMS.4406. 9. Shen J.T., Top M., Pei Y.T., Hosson M. Wear and friction performance of PTFE fi lled epoxy composites with a high concentration of SiO2 particles. Wear, 2015, vol. 322–323, no. 15, pp. 171–180. DOI: 10.1016/j. wear.2014.11.015. 10. Shen M., Li B., Zhang Z., Zhao L. Abrasive wear behavior of PTFE for seal applications under abrasiveatmosphere sliding condition. Friction, 2020, vol. 8, pp. 755–767. DOI: 10.1007/s40544-019-0301-7. 11. Sawyer W.G., Freudenberg K.D., Bhimaraj P., Schadler L.S. A study on the friction and wear behavior of PTFE fi lled with alumina nanoparticles. Wear, 2003, vol. 254, pp. 573–580. DOI: 10.1016/S0043-1648(03)00252-7. 12. Kim D.W, Kim K.W. Effects of sliding velocity and normal load on friction and wear characteristics of multi-layered diamond-like carbon (DLC) coating prepared by reactive sputtering. Wear, 20013, vol. 297, no. 1–2, pp. 722–730. DOI: 10.1016/j.wear.2012.10.009. 13. Wang M., Zhang C., Wang X. The wear behavior of textured steel sliding against polymers. Materials, 2017, vol. 10, no. 330, pp. 1–14. DOI: 10.3390/ma10040330. 14. Desale D.D., Pawar H.B. Performance analysis of Polytetrafl uoroethylene as journal bearing material. Procedia Manufacturing, 2018, vol. 20, pp. 414–419. DOI: 10.1016/j.promfg.2018.02.060 15. Ibrahim M.A., Şahin Y., Ibrahim A., Gidado A.Y., Yahya M.N. Specifi c wear rate modeling of polytetrafl ouroethylene composites via artifi cial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) tools. Virtual Assistant, IntechOpen, 2021. DOI: 10.5772/intechopen.95242. 16. Paturi U.M., Cheruku S., Reddy N.S. The role of artifi cial neural networks in prediction of mechanical and tribological properties of composites – A comprehensive review. Archives of Computational Methods in Engineering, 2022, vol. 29, pp. 1–41. DOI: 10.1007/s11831-021-09691-7. 17. Mahmood M.A., VisanA.I., Ristoscu C., Mihailescu I.N. Artifi cial neural network algorithms for 3D printing. Materials, 2020, vol. 14, no. 1, p. 163. DOI: 10.3390/ma14010163. 18. Naderpour H., Kheyroddin A., Amiri G.G. Prediction of FRP-confi ned compressive strength of concrete using artifi cial neural networks. Composite Structures, 2010, vol. 92, no. 12, pp. 2817–2829. DOI: 10.1016/j. compstruct.2010.04.008. Confl icts of Interest The author declare no confl ict of interest. 2022 The Author. Published by Novosibirsk State Technical University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
RkJQdWJsaXNoZXIy MTk0ODM1