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Velmurugan, Samikkannu, Raja Murugan, Thavidan Vellaiyan, Subravel, Visvalingam. (1405). Prediction and Parametric Effect in Drilling of Natural Fiber Laminate Using Combined Taguchi- Artificial Neural Network Approach. هنرهای کاربردی, 13(2), 415-426. doi: 10.22075/macs.2025.36924.1804
Samikkannu Velmurugan; Thavidan Vellaiyan Raja Murugan; Visvalingam Subravel. "Prediction and Parametric Effect in Drilling of Natural Fiber Laminate Using Combined Taguchi- Artificial Neural Network Approach". هنرهای کاربردی, 13, 2, 1405, 415-426. doi: 10.22075/macs.2025.36924.1804
Velmurugan, Samikkannu, Raja Murugan, Thavidan Vellaiyan, Subravel, Visvalingam. (1405). 'Prediction and Parametric Effect in Drilling of Natural Fiber Laminate Using Combined Taguchi- Artificial Neural Network Approach', هنرهای کاربردی, 13(2), pp. 415-426. doi: 10.22075/macs.2025.36924.1804
Velmurugan, Samikkannu, Raja Murugan, Thavidan Vellaiyan, Subravel, Visvalingam. Prediction and Parametric Effect in Drilling of Natural Fiber Laminate Using Combined Taguchi- Artificial Neural Network Approach. هنرهای کاربردی, 1405; 13(2): 415-426. doi: 10.22075/macs.2025.36924.1804

Prediction and Parametric Effect in Drilling of Natural Fiber Laminate Using Combined Taguchi- Artificial Neural Network Approach

Mechanics of Advanced Composite Structures
مقاله 13، دوره 13، شماره 2 - شماره پیاپی 28، بهمن 2026، صفحه 415-426    اصل مقاله (799.13 K)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22075/macs.2025.36924.1804
نویسندگان
Samikkannu Velmurugan* 1؛ Thavidan Vellaiyan Raja Murugan1؛ Visvalingam Subravel2
1Department of Manufacturing Engineering, Annamalai University, Chidambaram, 608002, India
2Department of Mechanical Engineering, Government College of Engineering, Thanjavur, 613402, India
تاریخ دریافت: 29 بهمن 1403،  تاریخ بازنگری: 15 مهر 1404،  تاریخ پذیرش: 01 آذر 1404 
چکیده
The study investigates the prediction and parametric effects in drilling of Prosopis juliflora fiber (PJF)-reinforced epoxy resin hybrid composite using a combined Taguchi-artificial neural network (ANN) approach. The composite was prepared via hand lay-up technique with natural reinforcement including vetiver fiber (VF) and coir pith (CP). The effects of drill bit diameter (DBD), spindle speed (SS), and feed rate (FR) on thrust force (TF) and surface roughness (SR) were evaluated through a full factorial design. An ANN model developed using a feedforward backpropagation algorithm successfully predicted the responses. Analysis of variance (ANOVA) results revealed that the regression coefficient (R2) for TF and SR were 96.39% and 95.54%, respectively. The DBD and FR were identified as the most significant parameters influencing TF and SR, both significant at the 95% confidence level (p<0.05). The regression plot exhibited a strong correlation (R=0.9883) between the predicted and actual values, while the ANN model achieved a mean squared error (MSE) of 0.089758 within 2 epochs. TF and SR increased with higher DBD and FR but decreased with an increased SS, as indicated by the main effect plots. Scanning electron microscope (SEM) revealed drilling-induced mechanisms, including fiber pullout, delamination, matrix cracking, matrix debonding, and matrix deformation. The findings demonstrate enhanced machining performance, offering potential for industrial applications and future research on bio-composite materials.
کلیدواژه‌ها
Taguchi؛ Artificial Neural Network (ANN)؛ Hand lay-up technique؛ Surface Roughness (SR)؛ Scanning Electron Microscope (SEM)
مراجع
  1. Das, T.K., Ghosh, P. and Das, N.C., 2019. Preparation, development, outcomes, and application versatility of carbon fiber-based polymer composites: a review. Advanced Composites and Hybrid Materials, 2(2), pp. 214–233.
  2. Feng, Y., Hao, H., Lu, H., Chow, C.L. and Lau, D., 2024. Exploring the development and applications of sustainable natural fiber composites: a review from a nanoscale perspective. Composites Part B: Engineering, pp. 111369.
  3. Kasirajan, S., Umapathy, D., Chandrasekar, C., Aafrin, V., Jenitapeter, M., Udhyasooriyan, L. and Muthusamy, S., 2019. Preparation of poly(lactic acid) from Prosopis juliflora and incorporation of chitosan for packaging applications. Journal of Bioscience and Bioengineering, 128, pp. 323–331.
  4. Rajan, B.S., Balaji, M.S. and Saravanakumar, S.S., 2018. Effect of chemical treatment and fiber loading on physico-mechanical properties of Prosopis juliflora fiber-reinforced hybrid friction composite. Materials Research Express, 6, pp. 035302.
  5. Kuntoğlu, M. and Sağlam, H., 2019. Investigation of progressive tool wear for determining optimized machining parameters in turning. Measurement, 140, pp. 427–436.
  6. Rajamurugan, T.V., Shanmugam, K. and Palanikumar, K., 2013. Analysis of delamination in drilling glass fiber-reinforced polyester composites. Materials & Design, 45, pp. 80–87.
  7. Ganesan, V., Shanmugam, V., Alagumalai, V., Kaliyamoorthy, B., Das, O. and Misra, M., 2024. Optimisation of mechanical behaviour of Calotropis gigantea and Prosopis juliflora natural fibre-based hybrid composites by using Taguchi-grey relational analysis. Composites Part C: Open Access, 13, pp. 100433.
  8. Raja, T., Devarajan, Y., Dhanraj, G., Pandiaraj, S., Rahaman, M. and Thiruvengadam, M., 2024. Delamination analysis of drilling parameters on neem/banyan fiber–reinforced sawdust particulates hybrid polymer composite. Biomass Conversion and Biorefinery, 14, pp. 10747–10757.
  9. Lilly Mercy, J., Shaqir Tanvir, M. and Swaroopkanth, K., 2017. Experimental investigation and Taguchi optimisation of drilling properties on teak wood reinforced epoxy resin. Materials Science and Engineering Conference Series, 197, pp. 012063.
  10. Mohan Kumar, A., Rajasekar, R., Manoj Kumar, P., Parameshwaran, R., Karthick, A., Mohanavel, V. and Muhibbullah, M., 2021. Investigation of drilling process parameters of palmyra-based composite. Advances in Materials Science and Engineering, 2021, pp. 4222344.
  11. Rajaraman, G., Agasti, S.K. and Jenarthanan, M.P., 2020. Investigation on effect of process parameters on delamination during drilling of kenaf-banana fiber reinforced epoxy hybrid composite using Taguchi method. Polymer Composites, 41, pp. 994–1002.
  12. Boga, C. and Koroglu, T., 2021. Proper estimation of surface roughness using hybrid intelligence based on artificial neural network and genetic algorithm. Journal of Manufacturing Processes, 70, pp. 560-569.
  13. Bolat, Ç., Özdoğan, N., Çoban, S., Ergene, B., Akgün, İ.C. and Gökşenli, A., 2024. Estimation of cutting forces in CNC slot-milling of low-cost clay reinforced syntactic metal foams by artificial neural network modeling. Multidiscipline Modeling in Materials and Structures, 20(3), pp. 417-436.
  14. Elaiyarasan, U., Ananthi, N. and Sathiyamurthy, S., 2024. Prediction and parametric effect of electrical discharge layering of AZ31B magnesium alloy using response surface methodology-assisted artificial neural network. Bulletin of Materials Science, 47(2), pp. 109.
  15. Elaiyarasan, U., Satheeshkumar, V., Senthilkumar, C. and Nandakumar, C., 2022. Mathematical and artificial neural network model in composite electrode assisted electrical discharge coating. Surface Topography: Metrology and Properties, 10(2), pp. 025004.
  16. Mohan, N.S., Ramachandra, A. and Kulkarni, S.M., 2005. Machining of fiber-reinforced thermoplastics: influence of feed and drill size on thrust force and torque during drilling. Journal of Reinforced Plastics and Composites, 24, pp. 1247–1257.
  17. Yu, Z., Li, C., Kurniawan, R., Park, K.M. and Ko, T.J., 2019. Drill bit with a helical groove edge for clean drilling of carbon fiber-reinforced plastic. Journal of Materials Processing Technology, 274, pp. 116291.
  18. Rajamurugan, T.V., Shanmugam, K., Rajakumar, S. and Palanikumar, K., 2012. Modelling and analysis of thrust force in drilling of GFRP composites using response surface methodology (RSM). Procedia Engineering, 38, pp. 3757–3768.
  19. Rao, Y.S., Mohan, N.S., Shetty, N. and Acharya, S., 2023. Drilling response of carbon fabric/solid lubricant filler/epoxy hybrid composites: an experimental investigation. Journal of Composites Science, 7, pp. 46.
  20. Prakash, R. and Krishnaraj, V., 2021. Cutting tools for machining composites. In: Advances in Machining of Composite Materials: Conventional and Non-Conventional Processes. Springer International Publishing, Cham, pp. 485–515.
  21. Yalçın, B., Bolat, Ç., Ergene, B., Karakılınç, U., Yavaş, Ç., Öz, Y., Ercetin, A., Maraş, S. and Der, O., 2024. Effect of drilling parameters and tool diameter on delamination and thrust force in the drilling of high-performance glass/epoxy composites for aerospace structures with a new design drill. Polymers, 16(21), pp. 3011.
  22. Bolat, Ç., Karakılınç, U., Yalçın, B., Öz, Y., Yavaş, Ç., Ergene, B., Ercetin, A. and Akkoyun, F., 2023. Effect of drilling parameters and tool geometry on the thrust force and surface roughness of aerospace grade laminate composites. Micromachines, 14(7), pp. 1427.
  23. Lazar, M.B. and Xirouchakis, P., 2011. Experimental analysis of drilling fiber reinforced composites. International Journal of Machine Tools and Manufacture, 51, pp. 937–946.
  24. Rajamurugan, T.V., Rajaganapathy, C., Jani, S.P., Gurram, C.S., Allasi, H.L. and Damtew, S.Z., 2022. Analysis of drilling of coir fiber‐reinforced polyester composites using multifaceted drill bit. Advances in Materials Science and Engineering, 2022, pp. 9481566.
  25. Rao, Y.S., Mohan, N.S., Shetty, N. and Shivamurthy, B., 2019. Drilling and structural property study of multi-layered fiber and fabric reinforced polymer composite: a review. Materials and Manufacturing Processes, 34, pp. 1549–1579.
  26. Mohan Kumar, A., Rajasekar, R., Manoj Kumar, P., Parameshwaran, R., Karthick, A. and Muhibbullah, M., 2021. Comparative analysis of drilling behaviour of synthetic and natural fiber‐based composites. Advances in Materials Science and Engineering, 2021, pp. 9019334.
  27. Franz, G., Vantomme, P. and Hassan, M.H., 2022. A review on drilling of multilayer fiber-reinforced polymer composites and aluminum stacks: optimization of strategies for improving the drilling performance of aerospace assemblies. Fibers, 10, pp. 78.
  28. Xu, J., Geier, N., Shen, J., Krishnaraj, V. and Samsudeensadham, S., 2023. A review on CFRP drilling: fundamental mechanisms, damage issues, and approaches toward high-quality drilling. Journal of Materials Research and Technology, 24, pp.9677–9707.
  29. Ergene, B., Bolat, C., Karakilinc, U. and Irez, A.B., 2023. A comprehensive investigation of drilling performance of anisotropic stacked glass‐carbon fiber reinforced hybrid laminate composites. Polymer Composites, 44(5), pp. 2656-2670.
  30. Rathod, D., Rathod, M., Patel, R., Shahabaz, S.M., Shetty, S.D. and Shetty, N., 2021. A review on strengthening, delamination formation, and suppression techniques during drilling of CFRP composites. Cogent Engineering, 8, pp. 1941588.
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