MACHINING OF COMPOSITE MATERIALS: CHALLENGES, ADVANCES AND AI-DRIVEN SOLUTIONS

Authors

  • Mohd Shahneel Saharudin School of Computing and Engineering Technology, Robert Gordon University, Aberdeen AB10 7GE, UK
  • Syafawati Hasbi ᵃSchool of Computing and Engineering Technology, Robert Gordon University, Aberdeen AB10 7GE, UK ᵇDepartment of Mechanical Engineering, Faculty of Engineering, Universiti Pertahanan Nasional Malaysia, Kem Sungai Besi, 57000, Wilayah Persekutuan Kuala Lumpur, Malaysia
  • Muhammad Younas School of Computing and Engineering Technology, Robert Gordon University, Aberdeen AB10 7GE, UK
  • Asif Ullah Faculty of Mechanical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Swabi 23460, KPK, Pakistan

DOI:

https://doi.org/10.11113/jurnalteknologi.v88.23923

Keywords:

Composites, machining, delamination, sustainable machining strategies, AI-driven machining optimisation

Abstract

The demand for composite materials is increasing across industries like energy storage, aerospace, automotive, and healthcare, driven by their exceptional attributes such as high strength-to-weight ratios and resistance to corrosion. However, machining these materials presents significant challenges due to their heterogeneous and anisotropic structures, leading to complex tool-workpiece interactions, rapid tool wear, poor surface quality, and environmental concerns. This review explores recent advancements in machining techniques for composite materials, with a particular focus on addressing key challenges and leveraging artificial intelligence (AI) solutions. It serves as a comprehensive resource to enhance machining practices in modern composite manufacturing by optimising machining parameters. The paper concludes by pinpointing significant research gaps in hybrid machining and AI-driven strategies, suggesting promising avenues for enhancing high-precision surface machining of fibre-reinforced composites and propelling the field forward.

References

Saharudin, M. S., R. A. Ilyas, N. Awang, S. Hasbi, I. Shyha, and F. Inam. 2023. Advances in Sustainable Nanocomposites. Sustainability. 15(6): 5125. https://doi.org/10.3390/su15065125.

Gavalda Diaz, O., G. Garcia Luna, Z. Liao, and D. Axinte. 2019. The New Challenges of Machining Ceramic Matrix Composites (CMCs): Review of Surface Integrity. International Journal of Machine Tools and Manufacture. 139: 24–36. https://doi.org/10.1016/j.ijmachtools.2019.01.003.

Vigneshwaran, S., K. M. John, R. Deepak Joel Johnson, M. Uthayakumar, V. Arumugaprabu, and S. T. Kumaran. 2021. Conventional and Unconventional Machining Performance of Natural Fibre-Reinforced Polymer Composites: A Review. Journal of Reinforced Plastics and Composites. 40: 553–567. https://doi.org/10.1177/0731684420958103.

Raj, S. S. R., J. E. R. Dhas, and C. P. Jesuthanam. 2021. Challenges on Machining Characteristics of Natural Fiber-Reinforced Composites – A Review. Journal of Reinforced Plastics and Composites. 40. https://doi.org/10.1177/0731684420940773.

Shyha, I. S.; Soo, S. L.; Aspinwall, D. K.; Bradley, S.; Perry, R.; Shyha, I. S., S. L. Soo, D. K. Aspinwall, S. Bradley, R. Perry, P. Harden, and S. Dawson. 2011. Hole Quality Assessment Following Drilling of Metallic-Composite Stacks. International Journal of Machine Tools and Manufacture 51: 569–578. https://doi.org/10.1016/j.ijmachtools.2011.04.007.

Teng, X., W. Chen, D. Huo, I. Shyha, and C. Lin. 2018. Comparison of Cutting Mechanism When Machining Micro and Nano-Particles Reinforced SiC/Al Metal Matrix Composites. Composite Structures. 203: 636–647. https://doi.org/10.1016/j.compstruct.2018.07.076.

Rawal, S., A. M. Sidpara, and J. Paul. 2022. A Review on Micro Machining of Polymer Composites. Journal of Manufacturing Processes. 77: 87–113. https://doi.org/10.1016/j.jmapro.2022.03.014.

Kumar, M. N., M. Mahmoodi, M. TabkhPaz, S. S. Park, and X. Jin. 2017. Characterization and Micro End Milling of Graphene Nano Platelet and Carbon Nanotube Filled Nanocomposites. Journal of Materials Processing Technology. 249: 96–107. https://doi.org/10.1016/j.jmatprotec.2017.06.005.

Deshmukh, S. P., R. Shrivastava, and C. M. Thakar. 2022. Machining of Composite Materials through Advanced Machining Process. Materials Today: Proceedings. 52: 1078–1081. https://doi.org/10.1016/j.matpr.2021.10.495.

Dambhare, S. G., S. J. Deshmukh, and A. B. Borade. 2015. Machining Parameter Optimization in Turning Process for Sustainable Manufacturing. International Journal of Industrial Engineering Computations 6. https://doi.org/10.5267/j.ijiec.2015.3.002.

Adler, D. P., W. W. S. Hii, D. J. Michalek, and J. W. Sutherland. 2006. Examining the Role of Cutting Fluids in Machining and Efforts to Address Associated Environmental/Health Concerns. Machining Science and Technology. 10. https://doi.org/10.1080/10910340500534282.

Lee, J. H., J. C. Ge, and J. H. Song. 2021. Study on Burr Formation and Toolwear in Drilling CFRP and Its Hybrid Composites. Applied Sciences. 11. https://doi.org/10.3390/app11010384.

Liu, W., L. M. Peeke, M. Periyasamy, R. R. Campbell, and M. A. Hickner. 2023. Additive Manufacturing of Silicone Composite Structures with Continuous Carbon Fiber Reinforcement. Polymer Engineering & Science. 63. https://doi.org/10.1002/pen.26318.

Mahanty, M., P. Kumar, A. K. Singh, and A. Chattopadhyay. 2020. Dynamic Response of an Irregular Heterogeneous Anisotropic Poroelastic Composite Structure Due to Normal Moving Load. Acta Mechanica 231. https://doi.org/10.1007/s00707-020-02649-z.

Fu, G., D. Huo, I. Shyha, K. Pancholi, and B. Alzahrani. 2020. Experimental Investigation on Micromachining of Epoxy/Graphene Nano Platelet Nanocomposites. International Journal of Advanced Manufacturing Technology. 107: 3169–3183. https://doi.org/10.1007/s00170-020-05190-4.

Fu, G., D. Huo, I. Shyha, F. Sun, and Q. Gao. 2022. Machinability Investigation of Polymer/GNP Nanocomposites in Micro-Milling. International Journal of Advanced Manufacturing Technology. 119. https://doi.org/10.1007/s00170-021-08471-8.

Shyha, I. S., D. K. Aspinwall, S. L. Soo, and S. Bradley. 2009. Drill Geometry and Operating Effects When Cutting Small Diameter Holes in CFRP. International Journal of Machine Tools and Manufacture. 49: 1008–1014. https://doi.org/10.1016/j.ijmachtools.2009.05.009.

Ramírez, G., J. M. Gonzalez Castro, J. Orrit-Prat, R. Bonet, N. Cuadrado, M. Vilaseca, L. Carreras, and J. Caro. 2022. Super-Hard DLC Coatings as an Alternative to Polycrystalline Diamond for Cutting Tools: Predictive Analysis of Aluminium Alloy Surface Quality. Lubricants. 10. https://doi.org/10.3390/lubricants10070135.

Devan, D. J., F. Almaskari, J. Sheikh-Ahmad, and F. Hafeez. 2022. A Study on Tool Wear of Tungsten Carbide Cutters in Edge Trimming of CFRP. Journal of Mechanical Science and Technology. 36. https://doi.org/10.1007/s12206-022-0432-z.

Okafor, C. E., S. Iweriolor, O. I. Ani, S. Ahmad, S. Mehfuz, G. O. Ekwueme, O. E. Chukwumuanya, S. E. Abonyi, I. E. Ekengwu, and O. P. Chikelu. 2023. Advances in Machine Learning-Aided Design of Reinforced Polymer Composite and Hybrid Material Systems. Hybrid Advances. 2. https://doi.org/10.1016/j.hybadv.2023.100026

Chen, C. T., and G. X. Gu. 2019. Machine Learning for Composite Materials. MRS Communications. 9. https://doi.org/10.1557/mrc.2019.32.

Jemielniak, K. 2021. Review of New Developments in Machining of Aerospace Materials. Journal of Machine Engineering. 21. https://doi.org/10.36897/jme/132905.

Pimenov, D. Y., M. Mia, M. K. Gupta, A. R. Machado, Í. V. Tomaz, M. Sarikaya, S. Wojciechowski, T. Mikołajczyk, and W. Kaplonek. 2021. Improvement of Machinability of Ti and Its Alloys Using Cooling–Lubrication Techniques: A Review and Future Prospect. Journal of Materials Research and Technology. 11.

Thirugnanasambantham, K. G., T. Sankaramoorthy, M. Kesava Reddy, and M. Pragada Venkata Sesha Aditya. 2022. A Review: Analysis of Load Transfer Effect in Carbon Nanotube (CNT) Reinforced Aluminium (Al) Composites. Materials Today: Proceedings. 60. https://doi.org/10.1016/j.matpr.2021.11.066.

Mourya, P., R. N. Goswami, R. Saini, A. Ray, and O. P. Khatri. 2024. Epoxy Coating Reinforced with Graphene–PANI Nanocomposites for Enhancement of Corrosion-Resistance Performance of Mild Steel in Saline Water. Colloids and Surfaces A: Physicochemical and Engineering Aspects. 133500. https://doi.org/10.1016/j.colsurfa.2024.133500.

Zhao, Q., Z. Lu, Y. Wu, and W. Zhao. 2022. Designing Strong Interfacial Adhesion between Carbon Fiber and Epoxy Resin via Dopamine towards Excellent Protection Ability under High Hydrostatic Pressure and Severe Erosion Corrosion Condition. Composites Science and Technology 217.

Hu, H. 2020. Recent Advances of Polymeric Phase Change Composites for Flexible Electronics and Thermal Energy Storage System. Composites Part B: Engineering. 195. https://doi.org/10.1016/j.compositesb.2020.108094.

Salifu, S., D. Desai, O. Ogunbiyi, and K. Mwale. 2022. Recent Development in the Additive Manufacturing of Polymer-Based Composites for Automotive Structures: A Review. International Journal of Advanced Manufacturing Technology. 119. https://doi.org/10.1007/s00170-021-08569-z.

Ravishankar, B., S. K. Nayak, and M. A. Kader. 2019. Hybrid Composites for Automotive Applications: A Review. Journal of Reinforced Plastics and Composites. 38. https://doi.org/10.1177/0731684419849708.

Abeselom, E., L. Gebrehiwet, E. Abate, Y. Negussie, and T. Teklehaymanot. 2023. Application of Composite Materials in Aerospace and Automotive Industry: Review. International Journal of Advances in Engineering and Management (IJAEM). 5.

Barbero, E. J. 2017. Introduction to Composite Materials Design. 3rd ed.

Jimmy, J., and B. Kandasubramanian. 2020. MXene Functionalized Polymer Composites: Synthesis and Applications. European Polymer Journal. 122. https://doi.org/10.1016/j.eurpolymj.2019.109367.

Shubham, and B. C. Ray. 2024. Introduction to Composite Materials. In Engineering Materials, Part F2264. https://doi.org/10.1007/978-981-99-9746-6_1.

Yi, X. S. 2017. An Introduction to Composite Materials. Composite Materials Engineering. 1. https://doi.org/10.1007/978-981-10-5696-3_1.

Jweeg, M. J., A. S. Hammood, and M. Al-Waily. 2012. Experimental and Theoretical Studies of Mechanical Properties for Reinforcement Fiber Types of Composite Materials. International Journal of Mechanical and Mechatronics Engineering. 12.

Janjua, A. A., M. Younas, R. A. Ilyas, I. Shyha, N. H. Faisal, F. Inam, and M. S. Saharudin. 2024. Optimizing DMF Utilization for Improved MXene Dispersions in Epoxy Nanocomposites. Journal of Composites Science. 8: 340. https://doi.org/10.3390/jcs8090340.

Zhang, J., V. S. Chevali, H. Wang, and C.-H. Wang. 2020. Current Status of Carbon Fibre and Carbon Fibre Composites Recycling. Composites Part B: Engineering 193: 1–15. https://doi.org/10.1016/j.compositesb.2020.108053.

Okolo, C., R. Rafique, S. S. Iqbal, T. Subhani, M. S. Saharudin, B. R. Bhat, and F. Inam. 2019. Customizable Ceramic Nanocomposites Using Carbon Nanotubes. Molecules. 24. https://doi.org/10.3390/molecules24173176.

Jeong, Y. J., H. T. Kim, J. D. Kim, J. H. Kim, S. K. Kim, and J. M. Lee. 2023. Evaluation of Mechanical Properties of Glass Fiber-Reinforced Composites Depending on Length and Structural Anisotropy. Results in Engineering. 17. https://doi.org/10.1016/j.rineng.2023.101000.

Karnati, S. R., P. Agbo, and L. Zhang. 2020. Applications of Silica Nanoparticles in Glass/Carbon Fiber-Reinforced Epoxy Nanocomposite. Composites Communications. 17. https://doi.org/10.1016/j.coco.2019.11.003.

Wada, T., H. Churei, M. Yokose, N. Iwasaki, H. Takahashi, and M. Uo. 2021. Application of Glass Fiber and Carbon Fiber-Reinforced Thermoplastics in Face Guards. Polymers 13(1). https://doi.org/10.3390/polym13010018.

Sathishkumar, T. P., S. Satheeshkumar, and J. Naveen. 2014. Glass Fiber-Reinforced Polymer Composites: A Review. Journal of Reinforced Plastics and Composites. 33. https://doi.org/10.1177/0731684414530790.

Y., Y. Song, D. Wu, X. Mao, X. Yang, S. Jiang, C. Zhang, and R. Guo. 2023. Recent Progress in Modifications, Properties, and Practical Applications of Glass Fiber. Molecules. 28. https://doi.org/10.3390/molecules28062466.

Jiao, J., X. Cheng, J. Wang, L. Sheng, Y. Zhang, J. Xu, C. Jing, S. Sun, H. Xia, and H. Ru. 2023. A Review of Research Progress on Machining Carbon Fiber-Reinforced Composites with Lasers. Micromachines. 14. https://doi.org/10.3390/mi14010024.

Strąg, M., and W. Swiderski. 2023. Defect Detection in Aramid Fiber-Reinforced Composites via Terahertz Radiation. Journal of Nondestructive Evaluation. 42. https://doi.org/10.1007/s10921-022-00917-7.

Guler, O., and N. Bagci. 2020. A Short Review on Mechanical Properties of Graphene Reinforced Metal Matrix Composites. Journal of Materials Research and Technology. 9. https://doi.org/10.1016/j.jmrt.2020.01.077.

Kim, J., L. Zani, A. Abdul-Kadir, L. Jones, A. Roy, L. Zhao, and V. V. Silberschmidt. 2022. Hybrid-Hybrid Machining of SiC-Reinforced Aluminium Metal Matrix Composite. Manufacturing Letters. 32. https://doi.org/10.1016/j.mfglet.2022.04.002.

Garg, P., A. Jamwal, D. Kumar, K. K. Sadasivuni, C. M. Hussain, and P. Gupta. 2019. Advance Research Progresses in Aluminium Matrix Composites: Manufacturing and Applications. Journal of Materials Research and Technology. 8. https://doi.org/10.1016/j.jmrt.2019.06.028.

Ujah, C. O., and D. V. Kallon. 2022. Trends in Aluminium Matrix Composite Development. Crystals. 12. https://doi.org/10.3390/cryst12101357.

Zhang, C., Z. Li, J. Zhang, H. Tang, and H. Wang. 2023. Additive Manufacturing of Magnesium Matrix Composites: Comprehensive Review of Recent Progress and Research Perspectives. Journal of Magnesium and Alloys. 11. https://doi.org/10.1016/j.jma.2023.02.005.

Xu, L. J., Y. F. Zheng, Z. Q. Liang, S. W. Han, X. Xue, S. L. Xiao, J. Tian, and Y. Y. Chen. 2023. Creep Behavior and Microstructure Evolution of Titanium Matrix Composites Reinforced with TiB, TiC and Y₂O₃. Transactions of Nonferrous Metals Society of China. 33. https://doi.org/10.1016/S1003-6326(22)66120-X.

Cao, H. C., and Y. L. Liang. 2020. The Microstructures and Mechanical Properties of Graphene-Reinforced Titanium Matrix Composites. Journal of Alloys and Compounds. 812. https://doi.org/10.1016/j.jallcom.2019.152057.

Guo, S., Y. Li, J. Gu, J. Liu, Y. Peng, P. Wang, Q. Zhou, and K. Wang. 2023. Microstructure and Mechanical Properties of Ti6Al4V/B₄C Titanium Matrix Composite Fabricated by Selective Laser Melting. Journal of Materials Research and Technology. 23. https://doi.org/10.1016/j.jmrt.2023.01.126.

Du, B., C. Han, Z. Li, C. Han, J. Li, M. Xiao, and Z. Yang. 2021. Effect of Polarity-Reversal Voltage on Charge Accumulation and Carrier Mobility in Silicone Rubber/Silicon Carbide Composites. IET Science, Measurement and Technology. 15. https://doi.org/10.1049/smt2.12020.

Szczęśniak, B., S. Głowniak, J. Choma, and M. Jaroniec. 2022. Mesoporous Carbon–Alumina Composites, Aluminas and Carbons Prepared via a Facile Ball Milling-Assisted Strategy. Microporous and Mesoporous Materials. 346. https://doi.org/10.1016/j.micromeso.2022.112325.

Bella, M. L., M. Hamidouche, and L. Gremillard. 2021. Preparation of Mullite–Alumina Composite by Reaction Sintering between Algerian Kaolin and Amorphous Aluminum Hydroxide. Ceramics International. 47. https://doi.org/10.1016/j.ceramint.2021.02.199.

Zygmuntowicz, J., J. Tomaszewska, R. Żurowski, M. Wachowski, P. Piotrkiewicz, and K. Konopka. 2021. Zirconia–Alumina Composites Obtained by Centrifugal Slip Casting as Attractive Sustainable Material for Application in Construction. Materials. 14. https://doi.org/10.3390/ma14020250.

Aydin, H., and G. Tokatas. 2019. Characterization and Production of Slip Cast Mullite–Zirconia Composites. SN Applied Sciences. 1. https://doi.org/10.1007/s42452-018-0061-4.

Coppola, B., T. Lacondemine, C. Tardivat, L. Montanaro, and P. Palmero. 2021. Designing Alumina–Zirconia Composites by DLP-Based Stereolithography: Microstructural Tailoring and Mechanical Performances. Ceramics International. 47. https://doi.org/10.1016/j.ceramint.2021.01.204.

Magnani, G., P. Fabbri, E. Leoni, E. Salernitano, and F. Mazzanti. 2021. New Perspectives on Zirconia Composites as Biomaterials. Journal of Composites Science. 5. https://doi.org/10.3390/jcs5090244.

Haris, N. I. N., M. Z. Hassan, R. A. Ilyas, M. A. Suhot, S. M. Sapuan, R. Dolah, R. Mohammad, and M. R. M. Asyraf. 2022. Dynamic Mechanical Properties of Natural Fiber Reinforced Hybrid Polymer Composites: A Review. Journal of Materials Research and Technology. 19. https://doi.org/10.1016/j.jmrt.2022.04.155.

Supian, A. B. M., M. Jawaid, B. Rashid, H. Fouad, N. Saba, H. N. Dhakal, and R. Khiari. 2021. Mechanical and Physical Performance of Date Palm/Bamboo Fibre Reinforced Epoxy Hybrid Composites. Journal of Materials Research and Technology. 15. https://doi.org/10.1016/j.jmrt.2021.08.115.

Bekele, A. E., H. G. Lemu, and M. G. Jiru. 2023. Study of the Effects of Alkali Treatment and Fiber Orientation on Mechanical Properties of Enset/Sisal Polymer Hybrid Composite. Journal of Composites Science. 7. https://doi.org/10.3390/jcs7010037.

Suriani, M. J., H. Z. Rapi, R. A. Ilyas, M. Petrů, and S. M. Sapuan. 2021. Delamination and Manufacturing Defects in Natural Fiber-Reinforced Hybrid Composite: A Review. Polymers. 13. https://doi.org/10.3390/polym13081323.

Wei, J., M. S. Saharudin, T. Vo, and F. Inam. 2017. Dichlorobenzene: An Effective Solvent for Epoxy/Graphene Nanocomposites Preparation. Royal Society Open Science. 4. https://doi.org/10.1098/rsos.170778.

Saharudin, M. S., N. A. Che Nasir, and S. Hasbi. 2022. Tensile and Corrosion Resistance Studies of MXenes Nanocomposites: A Review. In Advanced Structured Materials. 167: 189–98. Springer. https://doi.org/10.1007/978-3-030-89988-2_14.

Saharudin, M. S., N. A. Che Nasir, and S. Hasbi. 2022. Tensile and Corrosion Resistance Studies of MXenes Nanocomposites: A Review. In Advanced Structured Materials. 167: 189–98. Springer. https://doi.org/10.1007/978-3-030-89988-2_14.

Casati, R., and M. Vedani. 2014. Metal Matrix Composites Reinforced by Nano-Particles: A Review. Metals. 4. https://doi.org/10.3390/met4010065.

Sun, J., D. Ye, J. Zou, X. Chen, Y. Wang, J. Yuan, H. Liang, H. Qu, J. Binner, and J. Bai. 2023. A Review on Additive Manufacturing of Ceramic Matrix Composites. Journal of Materials Science & Technology. 138. https://doi.org/10.1016/j.jmst.2022.06.039.

Zhang, L., Z. Wu, C. Wu, and Q. Wu. 2022. On the Numerical Modelling of Composite Machining. Composites Part B: Engineering. 241: 110023. https://doi.org/10.1016/j.compositesb.2022.110023.

Babu, J., L. Paul, and J. P. Davim. 2020. High Speed Machining of Composite Materials. In High-Speed Machining. https://doi.org/10.1016/B978-0-12-815020-7.00003-5.

Pasko, R., L. Przybylski, and B. Słodki. 2002. High Speed Machining (HSM)—The Effective Way of Modern Cutting. In Proceedings of the 7th DAAAM International Symposium. 1–6.

Zhang, J., X. Huang, X. Kang, H. Yi, Q. Wang, and H. Cao. 2023. Energy Field-Assisted High-Speed Dry Milling Green Machining Technology for Difficult-to-Machine Metal Materials. Frontiers of Mechanical Engineering. 18. https://doi.org/10.1007/s11465-022-0744-9.

Wang, B., Z. Liu, Y. Cai, X. Luo, H. Ma, Q. Song, and Z. Xiong. 2021. Advancements in Material Removal Mechanism and Surface Integrity of High-Speed Metal Cutting: A Review. International Journal of Machine Tools and Manufacture. 166: 103744. https://doi.org/10.1016/j.ijmachtools.2021.103744.

Sandström, D. R., and J. N. Hodowany. 1998. Modeling the Physics of Metal Cutting in High-Speed Machining. Machining Science and Technology. 2. https://doi.org/10.1080/10940349808945675.

Slamani, M., H. Chafai, and J.-F. Chatelain. 2024. Effect of Milling Parameters on the Surface Quality of a Flax Fiber-Reinforced Polymer Composite.” Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 238: 1537–1544. https://doi.org/10.1177/09544089221126087

Babu, J., T. Sunny, N. A. Paul, K. P. Mohan, J. Philip, and J. P. Davim. 2016. Assessment of Delamination in Composite Materials: A Review. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 230. https://doi.org/10.1177/0954405415619343.

Sousa, V. F. C., F. J. G. da Silva, G. F. Pinto, A. Baptista, and R. Alexandre. 2021. Characteristics and Wear Mechanisms of TiAlN-Based Coatings for Machining Applications: A Comprehensive Review. Metals. 11. https://doi.org/10.3390/met11020260.

Liang, X., and Z. Liu. 2018. Tool Wear Behaviors and Corresponding Machined Surface Topography during High-Speed Machining of Ti–6Al–4V with Fine Grain Tools. Tribology International. 121. https://doi.org/10.1016/j.triboint.2018.01.057.

Fegyverneki, S., A. Körei, and J. Kundrák. 2013. Parameter Approximation for Tool Life Equations. Production Systems and Information Engineering. 6.

Polishetty, A., M. Goldberg, and G. Littlefair. 2010. Wear Characteristics of Ultra-Hard Cutting Tools When Machining Austempered Ductile Iron. International Journal of Mechanical and Mechanics Engineering. 10.

Li, G., W. Bie, B. Zhao, F. Chen, C. Zhao, and Y. Zhang. 2022. Ultrasonic Assisted Machining of Gears with Enhanced Fatigue Resistance: A Comprehensive Review. Advances in Mechanical Engineering. 14. https://doi.org/10.1177/16878132221082849.

Abukhshim, N. A., P. T. Mativenga, and M. A. Sheikh. 2006. Heat Generation and Temperature Prediction in Metal Cutting: A Review and Implications for High-Speed Machining. International Journal of Machine Tools and Manufacture. 46. https://doi.org/10.1016/j.ijmachtools.2005.07.024.

Xu, S., T. Kuriyagawa, K. Shimada, and M. Mizutani. 2017. Recent Advances in Ultrasonic-Assisted Machining for the Fabrication of Micro/Nano-Textured Surfaces. Frontiers of Mechanical Engineering. 12. https://doi.org/10.1007/s11465-017-0422-5.

Li, G., W. Bie, B. Zhao, F. Chen, C. Zhao, and Y. Zhang. 2022. Ultrasonic Assisted Machining of Gears with Enhanced Fatigue Resistance: A Comprehensive Review. Advances in Mechanical Engineering. 14. https://doi.org/10.1177/16878132221082849.

Kuşhan, M. C., S. Orak, and Y. Uzunonat. 2017. Ultrasonic Assisted Machining Methods: A Review. International Journal of Advanced Engineering Research and Applications (IJA-ERA). 3(5).

Yang, Z., L. Zhu, G. Zhang, C. Ni, and B. Lin. 2020. Review of Ultrasonic Vibration-Assisted Machining in Advanced Materials. International Journal of Machine Tools and Manufacture 156: 103594.

https://doi.org/10.1016/j.ijmachtools.2020.103594.

Dixit, U. S., P. M. Pandey, and G. C. Verma. 2019. Ultrasonic-Assisted Machining Processes: A Review. International Journal of Mechatronics and Manufacturing Systems. 12(3–4): 226–250.

https://doi.org/10.1504/IJMMS.2019.103479

Juri, Afifah Z., Renan Belli, Ulrich Lohbauer, Heike Ebendorff-Heidepriem, and Ling Yin. 2023. Edge Chipping Damage in Lithium Silicate Glass-Ceramics Induced by Conventional and Ultrasonic Vibration-Assisted Diamond Machining. Dental Materials 39 (6): 557–567. https://doi.org/10.1016/j.dental.2023.04.001.

Qin, N., J. Lei, and Z. J. Pei. 2016. Experimental Investigations on Core Drilling by Ultrasonic-Vibration-Assisted Grinding for Hard-to-Machine Materials—A Review. International Journal of Manufacturing Research. 11(1–2): 131–154. https://doi.org/10.1504/IJMR.2016.076976.

Martins, H., and H. Puga. 2023. Ultrasonic Assisted Machining Overview: Accessing Feasibility and Overcoming Challenges for Milling Applications. Metals. 13(5): 908. https://doi.org/10.3390/met13050908.

Chandrasekar, S., A. Z. Juri, M. A. R. K. Kumar, A. R. P. S. K. Ramesh, and R. Venkatesh. 2023. Overview of Electric Discharge Machining of Machine-Tooled Ceramics and Ceramic-Based Composites. REST Journal on Emerging Trends in Modelling and Manufacturing. 9(1): 37–46. https://doi.org/10.46632/jemm/9/2/2.

Singh, M., S. Singh, and S. Kumar. 2020. Investigating the Impact of LASER Assistance on the Accuracy of Micro-Holes Generated in Carbon Fiber Reinforced Polymer Composite by Electrochemical Discharge Machining. Journal of Manufacturing Processes. 60: 644–654. https://doi.org/10.1016/j.jmapro.2020.10.056.

Kukliński, M., D. Przestacki, A. Bartkowska, P. Kieruj, and N. Radek. 2023. Conventional and Laser-Assisted Machining of Laser-Borided Monel 400 Alloy. International Journal of Advanced Manufacturing Technology. 126. https://doi.org/10.1007/s00170-023-11477-z.

Xu, D., Z. Liao, D. Axinte, J.A. Sarasua, R. M'Saoubi, and A. Wretland. 2020. Investigation of Surface Integrity in Laser-Assisted Machining of Nickel Based Superalloy. Materials & Design. 194. https://doi.org/10.1016/j.matdes.2020.108851.

You, K., G. Yan, X. Luo, M. D. Gilchrist, and F. Fang. 2020. Advances in Laser Assisted Machining of Hard and Brittle Materials. Journal of Manufacturing Processes. 58. https://doi.org/10.1016/j.jmapro.2020.08.034.

Erdenechimeg, K., H. I. Jeong, and C. M. Lee. 2019. A Study on the Laser-Assisted Machining of Carbon Fiber Reinforced Silicon Carbide. Materials. 12. https://doi.org/10.3390/ma12132061.

Kong, X., Z. Dang, X. Liu, and M. Wang. 2023. A Comparative Evaluation of Laser Assisted Drilling CFRP with Improved Machining Mechanism. Journal of Materials Processing Technology. 321. https://doi.org/10.1016/j.jmatprotec.2023.118156.

Dahiya, A. K., B. K. Bhuyan, and S. Kumar. 2022. Perspective Study of Abrasive Water Jet Machining of Composites - A Review. Journal of Mechanical Science and Technology. 36. https://doi.org/10.1007/s12206-021-1220-x.

Nanjundeswaraswamy, T. S., A. Professor. 2019. A Literature Review on Parameters Influencing Abrasive Jet Machining and Abrasive Water Jet Machining. Varun R Journal of Engineering Research and Application. 9. https://doi:10.9790/9622-0901012429.

Bañon, F., A. Sambruno, L. González-Rovira, J.M. Vazquez-Martinez, and J. Salguero. 2021. A Review on the Abrasive Water-Jet Machining of Metal-Carbon Fiber Hybrid Materials. Metals. 11. https://doi.org/10.3390/met11010164.

Abushanab, W. S., E. B. Moustafa, M. Harish, S. Shanmugan, and A. H. Elsheikh. 2022. Experimental Investigation on Surface Characteristics of Ti6Al4V Alloy during Abrasive Water Jet Machining Process. Alexandria Engineering Journal. 61. https://doi.org/10.1016/j.aej.2022.01.004.

Kumar, S. P., A. S. Shata, K. V. P. Kumar, R. Sharma, H. Munnur, M. L. Rinawa, and S. S. Kumar. 2022. Effect on Abrasive Water Jet Machining of Aluminum Alloy 7475 Composites Reinforced with CNT Particles. Materials Today: Proceedings. 59. https://doi.org/10.1016/j.matpr.2022.01.095.

Reddy, S. 2023. An Introduction to Artificial Intelligence. In Translational Application of Artificial Intelligence in Healthcare: A Textbook. https://doi.org/10.1201/9781003262152.

Callier, P., and O. Sandel. 2021. Introduction to Artificial Intelligence. Actualites Pharmaceutiques. 60. https://doi.org/10.1016/j.actpha.2021.10.005.

Wang, Y., K. Wang, and C. Zhang. 2024. Applications of Artificial Intelligence Machine Learning to High-Performance Composites. Composites Part B. 285: 1–21. https://doi.org/10.1016/j.compositesb.2024.111740.

Kubat, M. 2021. An Introduction to Machine Learning. https://doi.org/10.1007/978-3-030-81935-4.

Badillo, S., B. Banfai, F. Birzele, I. I. Davydov, L. Hutchinson, T. Kam-Thong, J. Siebourg-Polster, B. Steiert, and J. D. Zhang. 2020. An Introduction to Machine Learning. Clinical Pharmacology & Therapeutics. 107. https://doi.org/10.1002/cpt.1796.

Bellodi, E., R. Zese, F. Riguzzi, and E. Lamma. 2022. Introduction to Machine Learning. In Machine Learning and Non-volatile Memories. https://doi.org/10.1007/978-3-031-03841-9_1.

Pankaj, S., S. Kant, C. S. Jawalkar, S.K. Khatkar, M. Singh, and M. K. Jindal. 2024. Experimental Investigation on Mechanical Performance and Drilling Behavior of Hybrid Polymer Composites through Statistical and Machine Learning Approach. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. https://doi.org/10.1177/09544089231223022.

Popan, I. A., V. I. Bocăneț, S. Softic, A. I. Popan, N. Panc, and N. Balc. 2024. Artificial Intelligence Model Used for Optimizing Abrasive Water Jet Machining Parameters to Minimize Delamination in Carbon Fiber-Reinforced Polymer. Applied Sciences. 14. https://doi.org/10.3390/app14188512.

Tzotzis, A., D. Nedelcu, S.N. Mazurchevici, and P. Kyratsis. 2024. Surface Quality Evaluation of 3D-Printed Carbon-Fiber-Reinforced PETG Polymer During Turning: Experimental Analysis, ANN Modeling and Optimization. Polymers. 16. https://doi.org/10.3390/polym16202927.

Nargis, T., S.M. Shahabaz, S. Acharya, N. Shetty, R.L. Malghan, and S.D. Shetty. 2024. A Comprehensive Study on the Optimization of Drilling Performance in Hybrid Nano-Composites and Neat CFRP Composites Using Statistical and Machine Learning Approaches. Journal of Manufacturing and Materials Processing. 8. https://doi.org/10.3390/jmmp8020067.

Gadagi, A., B. Sivaprakash, C. Adake, U. Deshannavar, P. G. Hegde, S. P., N. Rajamohan, and A. I. Osman. 2024. Epoxy Composite Reinforced with Jute/Basalt Hybrid - Characterisation and Performance Evaluation Using Machine Learning Techniques. Composites Part C: Open Access. 14. https://doi.org/10.1016/j.jcomc.2024.100453.

Vinoth, V., S. Sathiyamurthy, S. Saravanakumar, and R. Senthilkumar. 2024. Integrating Response Surface Methodology and Machine Learning for Analyzing the Unconventional Machining Properties of Hybrid Fiber-Reinforced Composites. Polymer Composites. 45: 6077–6092. https://doi.org/10.1002/pc.28180

Ma, Q., Y. Zhong, Z. Wang, and S. Bukkapatnam. 2024. Effect of Microstructure on the Machinability of Natural Fiber Reinforced Plastic Composites: A Novel Explainable Machine Learning (XML) Approach. Journal of Manufacturing Science and Engineering. 146. https://doi.org/10.1115/1.4064039.

Karim, M. R., S. M. Ashiquzzaman Nipu, M. S. Hossain Shawon, R. Kumar, S. Salman, A. Verma, E. S. M. Sherif, S. Islam, and M. I. Ammarullah. 2024. Machinability Investigation of Natural Fibers Reinforced Polymer Matrix Composite under Drilling: Leveraging Machine Learning in Bioengineering Applications. AIP Advances. 14. https://doi.org/10.1063/5.0200625.

Saravanakumar, S., S. Sathiyamurthy, and V. Vinoth. 2024. Enhancing Machining Accuracy of Banana Fiber-Reinforced Composites with Ensemble Machine Learning. Measurement. 235. https://doi.org/10.1016/j.measurement.2024.114912.

Biruk-Urban, K., P. Bere, and J. Józwik. 2023. Machine Learning Models in Drilling of Different Types of Glass-Fiber-Reinforced Polymer Composites. Polymers. 15(23): 4609 https://doi.org/10.3390/polym15234609.

Aveen, K. P., N. Londhe, V. N. Ullal, and K. M. Pranesh Rao. 2023. Effect of Aluminium Filler Concentration on Delamination in GFRP Composite with Optimized Machining Conditions Using ANN-Genetic Algorithm. Engineering Research Express. 5. https://doi.org/10.1088/2631-8695/acc2a1.

Abd-Elwahed, M. S. 2023. Multi-Objective Optimization of Drilling GFRP Composites Using ANN Enhanced by Particle Swarm Algorithm. Processes. 11. https://doi.org/10.3390/pr11082418.

Jenarthanan, M. P., B. Harinesh, and U. Arunachalam. 2023. Modelling and Prediction of Machining Forces During End Milling of Glass Fibre Reinforced Polymer Composites Using Regression Analysis and Artificial Neural Networks (ANN). Engineered Science. 23. https://doi.org/10.30919/es8d869.

Mohan, N., S. A. Kalam, R. Mahaveerkannan, M. Shah, J. S. Yadav, V. Sharma, P. S. Naik, and D. B. Narasimha. 2022. Statistical Evaluation of Machining Parameters in Drilling of Glass Laminate Aluminum Reinforced Epoxy Composites Using Machine Learning Model. Engineered Science. 20. https://doi.org/10.30919/es8e716.

Kamath, G., B. Mishra, S. Tiwari, A. Bhardwaj, S. S. Marar, S. Soni, R. Chauhan, and S. B. Anjappa. 2022. Experimental and Statistical Evaluation of Drilling Induced Damages in Glass Fiber Reinforced Polymer Composites - Taguchi Integrated Supervised Machine Learning Approach. Engineered Science. 19: 312–318. https://doi.org/10.30919/es8d733.

Jin, F., Y. Bao, B. Li, and X. Jin. 2022. Tool Wear Prediction in Edge Trimming of Carbon Fiber Reinforced Polymer Using Machine Learning with Instantaneous Parameters. Journal of Manufacturing Processes. 82: 277–295. https://doi.org/10.1016/j.jmapro.2022.08.006.

Abd-Elwahed, M. S. 2022. Drilling Process of GFRP Composites: Modeling and Optimization Using Hybrid ANN. Sustainability. 14. https://doi.org/10.3390/su14116599.

Rajasekaran, T., K. Palanikumar, and B. Latha. 2022. Investigation and Analysis of Surface Roughness in Machining Carbon Fiber Reinforced Polymer Composites Using Artificial Intelligence Techniques. Carbon Letters. 32: 615–627. https://doi.org/10.1007/s42823-021-00298-3.

Belaadi, A., M. Boumaaza, H. Alshahrani, M. Bourchak, and M. Jawaid. 2022. Drilling Performance Prediction of HDPE/Washingtonia Fiber Biocomposite Using RSM, ANN, and GA Optimization. International Journal of Advanced Manufacturing Technology. 123. https://doi.org/10.1007/s00170-022-10248-6.

Pattanayak, S., A. K. Sahoo, and S. K. Sahoo. 2022. CFRP Composite Drilling through Electrical Discharge Machining Using Aluminum as Fixture Plate. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 236. https://doi.org/10.1177/09544062211058675.

Yardimeden, A. 2022. Estimating of Cutting Force and Surface Roughness in Turning of GFRP Composites with Different Orientation Angles Using Artificial Neural Network. Reviews on Advanced Materials Science. 61. https://doi.org/10.1515/rams-2022-0286.

Duboust, N., M. Watson, M. Marshall, G.E. O'Donnel, and K. Kerrigan. 2021. Towards Intelligent CFRP Composite Machining: Surface Analysis Methods and Statistical Data Analysis of Machined Fibre Laminate Surfaces. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 235: 1602–1617. https://doi.org/10.1177/0954405420960920.

Seo, J., D.Y. Kim, D.C. Kim, and H.W. Park. 2021. Recent Developments and Challenges on Machining of Carbon Fiber Reinforced Polymer Composite Laminates. International Journal of Precision Engineering and Manufacturing. 22. https://doi.org/10.1007/s12541-021-00596-w.

Prakash, S., and S. Suman. 2021. Neural Network-Based Prediction for Surface Characteristics in CO2 Laser Micro-Milling of Glass Fiber Reinforced Plastic Composite. Neural Computing and Applications. 33. https://doi.org/10.1007/s00521-021-05818-w.

Wang, Z., F. Chegdani, N. Yalamarti, B. Takabi, B. Tai, M. El Mansori, and S. Bukkapatnam. 2020. Acoustic Emission Characterization of Natural Fiber Reinforced Plastic Composite Machining Using a Random Forest Machine Learning Model. Journal of Manufacturing Science and Engineering, Transactions of the ASME. 142. https://doi.org/10.1115/1.4045945.

Caggiano, A., P. Centobelli, L. Nele, and R. Teti. 2017. Multiple Sensor Monitoring in Drilling of CFRP/CFRP Stacks for Cognitive Tool Wear Prediction and Product Quality Assessment. Procedia CIRP. 62. https://doi.org/10.1016/j.procir.2017.03.047.

Knittel, D., H. Makich, and M. Nouari. 2019. Milling Diagnosis Using Artificial Intelligence Approaches. Mechanics and Industry. 20. https://doi.org/10.1051/meca/2020053.

Codjo, L., M. Jaafar, H. Makich, D. Knittel, and M. Nouari. 2018. Honeycomb Core Milling Diagnosis Using Machine Learning in the Industry 4.0 Framework. In Proceedings of the IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. 2018-September. https://doi.org/10.1109/ETFA.2018.8502475

Kumaran, S. T., T. J. Ko, R. Kurniawan, C. Li, and M. Uthayakumar. 2017. ANFIS Modeling of Surface Roughness in Abrasive Waterjet Machining of Carbon Fiber Reinforced Plastics. Journal of Mechanical Science and Technology. 31. https://doi.org/10.1007/s12206-017-0741-9.

Jia, Z., Y. Su, B. Niu, B. Zhang, and F. Wang. 2016. The Interaction between the Cutting Force and Induced Sub-Surface Damage in Machining of Carbon Fiber-Reinforced Plastics. Journal of Reinforced Plastics and Composites. 35. https://doi.org/10.1177/0731684415626284.

Shaban, Y., S. Yacout, M. Balazinski, M. Meshreki, and H. Attia. 2015. Diagnosis of Machining Outcomes Based on Machine Learning with Logical Analysis of Data. In Proceedings of the IEOM 2015 - 5th International Conference on Industrial Engineering and Operations Management. https://doi.org/10.1109/IEOM.2015.7093752.

Qin, X., B. Wang, G. Wang, H. Li, Y. Jiang, and X. Zhang. 2014. Delamination Analysis of the Helical Milling of Carbon Fiber-Reinforced Plastics by Using the Artificial Neural Network Model. Journal of Mechanical Science and Technology. 28. https://doi.org/10.1007/s12206-013-1135-2.

Erkan, Ö., B. Işık, A. Çiçek, and F. Kara. 2013. Prediction of Damage Factor in End Milling of Glass Fibre Reinforced Plastic Composites Using Artificial Neural Network. Applied Composite Materials. 20: 517–536. https://doi.org/10.1007/s10443-012-9286-3.

Yacout, S., M. Meshreki, and H. Attia. 2012. Monitoring and Control of Machining Process by Data Mining and Pattern Recognition. In Proceedings of the 2012 6th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). https://doi.org/10.1109/CISIS.2012.211.

Kalla, D. K., J. Sheikh-Ahmad, and J. Twomey. 2012. ANN Applications in Machining of Fiber-Reinforced Composites. In Fiber-Reinforced Composites (AIP Conference Proceedings 2012). https://doi.org/10.1063/1.4707606.

Kalla, D., J. Sheikh-Ahmad, and J. Twomey. 2010. Prediction of Cutting Forces in Helical End Milling Fiber Reinforced Polymers. International Journal of Machine Tools and Manufacture. 50. https://doi.org/10.1016/j.ijmachtools.2010.06.005.

Sarma, P. M. M. S., L. Karunamoorthy, and K. Palanikumar. 2009. Surface Roughness Parameters Evaluation in Machining GFRP Composites by PCD Tool Using Digital Image Processing. Journal of Reinforced Plastics and Composites. 28. https://doi.org/10.1177/0731684408089858.

Karnik, S. R., V. N. Gaitonde, F. Mata, and J. P. Davim. 2008. Investigative Study on Machinability Aspects of Unreinforced and Reinforced PEEK Composite Machining Using ANN Model. Journal of Reinforced Plastics and Composites. 27. https://doi.org/10.1177/0731684407084259.

Tsao, C. C. 2007. Taguchi Analysis of Drilling Quality Associated with Core Drill in Drilling of Composite Material. International Journal of Advanced Manufacturing Technology. 32. https://doi.org/10.1007/s00170-006-0414-9.

Bagci, E., and B. Işik. 2006. Investigation of Surface Roughness in Turning Unidirectional GFRP Composites by Using RS Methodology and ANN. International Journal of Advanced Manufacturing Technology. 31: 10–17. https://doi.org/10.1007/s00170-005-0175-x.

Kalla, D., P. Lodhia, B. Bajracharya, J. Twomey, and J. Sheikh-Ahmad. 2005. CN Force Prediction Model in Milling of Carbon Fiber Reinforced Polymers. In Proceedings of Intelligent Systems in Design and Manufacturing VI. 5999. https://doi.org/10.1117/12.632100.

Dharan, C., and M. Won. 2000. Machining Parameters for an Intelligent Machining System for Composite Laminates. Composite Structures. 40. https://doi.org/10.1016/S0890-6955(99)00065-6.

Hoghoughi, M. H., M. Farahnakain, and S. Elhami. 2022. Environmental, Economical, and Machinability Based Sustainability Assessment in Hybrid Machining Process Employing Tool Textures and Solid Lubricant. Sustainable Materials and Technologies. 34. https://doi.org/10.1016/j.susmat.2022.e00511.

Mahbub, M. R., A. Rashid, and M. P. Jahan. 2021. Hybrid Machining and Finishing Processes. In Advanced Machining and Finishing. https://doi.org/10.1016/B978-0-12-817452-4.00019-1.

Kumar, J., R. K. Verma, A. K. Mondal, and V. K. Singh. 2021. A Hybrid Optimization Technique to Control the Machining Performance of Graphene/Carbon/Polymer (Epoxy) Nanocomposites. Polymers and Polymer Composites. 29. https://doi.org/10.1177/09673911211046789.

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2025-12-23

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