Journal of Polymer & Composites Original Research Special issue

Multi-Objective Optimization of Carbon-Glass Fiber Polymer Drilling Process Based on Fuzzy Grey Entropy Weighing Method

  1. Purna Surendernath Department of mechanical engineering, KoneruLakshmaiah Education Foundation, Vaddeshwaram
  2. P. Kasi V. Rao Department of Mechanical engineering, Koneru Lakshmaiah Education Foundation, vaddeswaram
  3. M. V. Satish Kumar Department of Mechanical engineering, Kamala institute of technology and science, Singapore
  4. M. Pradeep Kumar Department of Mechanical Engineering, JNTUH University College of Engineering Science & Technology, Hyderabad

Abstract

In recent years, the machining characteristics of hybrid fiber polymer composites have garnered significant research attention due to their growing industrial applications. This study specifically focuses on the drilling of hybrid carbon-glass fiber reinforced (CGFR) epoxy composites, fabricated using the hand layup technique. The key machining characteristics evaluated in this drilling process include surface roughness and circularity error. The influence of critical drilling process parameters, such as spindle speed, drill bit diameter, and point angle, on these characteristics was systematically investigated. A multi-objective optimization approach was employed to determine the optimal parameter combinations for drilling CGFR composites. The experimental design was based on the Taguchi method, considering spindle speed, drill bit diameter, and point angle as input parameters. The performance characteristics, such as surface roughness and circularity error, were analyzed using grey relational analysis integrated with a fuzzy inference system (FIS) to manage multiple responses effectively. The fuzzy inference system was utilized to convert the performance characteristics into a common factor level setting to optimize the machining process. The study's findings demonstrated that the optimal combination of drilling parameters significantly minimized both surface roughness and circularity error, enhancing the overall quality of the drilled hybrid composite.

Keywords

References (31)

  1. Slamani M, Chatelain JF. A review on the machining of polymer composites reinforced with carbon (CFRP), glass (GFRP), and natural fibers (NFRP). Discover Mechanical Engineering. 2023;2(1). doi:10.1007/s44245-023-00011-w
  2. Premnath K, Arunprasath K, Sanjeevi R, Elilvanan R, Ramesh M. Natural/synthetic fiber reinforced hybrid composites on their mechanical behaviors– a review. Interactions. 2024;245(1). doi:10.1007/s10751-024-01924-y
  3. Gonabadi H, Oila A, Yadav A, Bull S. Investigation of anisotropy effects in glass fibre reinforced polymer composites on tensile and shear properties using full field strain measurement and finite element multi-scale techniques. Journal of Composite Materials. 2022;56(3):507-524. doi:1177/00219983211054232
  4. T D Jagannatha1* and G Harish1, Mechanical Properties 0f Carbon/Glass Fiber Reinforced Epoxy Hybrid Polymer Composites, J. Mech. Eng. & Rob. Res. 2015,Vol. 4, No. 2, April 2015
  5. Muneer Ahmed M, Dhakal HN, Zhang ZY, Barouni A, Zahari R. Enhancement of impact toughness and damage behaviour of natural fibre reinforced composites and their hybrids through novel improvement techniques: A critical review. Composite Structures. 2021;259:113496. doi:10.1016/j.compstruct.2020.113496
  6. Amar K. Mohanty et al. Composites from renewable and sustainable resources: Challenges and innovations.Science362,536-542(2018).DOI:1126/science.aat9072
  7. Dong C. Flexural properties of symmetric carbon and glass fibre reinforced hybrid composite laminates. Composites Part C: Open Access. 2020;3:100047. doi:10.1016/j.jcomc.2020.100047
  8. Guermazi N, Haddar N, Elleuch K, Ayedi HF. Investigations on the fabrication and the characterization of glass/epoxy, carbon/epoxy and hybrid composites used in the reinforcement and the repair of aeronautic structures. Materials & Design (1980-2015). 2014;56:714-724. doi:10.1016/j.matdes.2013.11.043
  9. Song JH. Pairing effect and tensile properties of laminated high-performance hybrid composites prepared using carbon/glass and carbon/aramid fibers. Composites Part B: Engineering. 2015;79:61-66. doi:10.1016/j.compositesb.2015.04.015
  10. Kumar R, Navaneethakrishnan SVM, Solaiachari S. Investigation on Hybrid Glass-Carbon Fiber Composites Used in Solar Greenhouse Dryers. Fibers and Polymers. 2024;25(10):3995-4006. doi:10.1007/s12221-024-00719-w
  11. Abebe Y, Palani S, Sirahbizu B, Hossain N. Experimental investigation on mechanical properties and water absorption capacity of novel polyester-wool-glass fibre-reinforced hybrid polymer matrix composites. Biomass Conversion and Biorefinery. 2023;15(19):26231-26241. doi:10.1007/s13399-023-04599-7
  12. Erkendirci ÖF, Avcı A, Dahil L, Kaya K, Kılıçtek S, Sezgin A. Experimental Investigation of Tensile and Impact Response of Nano-Alumina-Filled Epoxy Hybrid Composites Reinforced with Carbon-Kevlar and Carbon-Glass Fabrics. Arabian Journal for Science and Engineering. 2022;47(12):16135-16148. doi:10.1007/s13369-022-06848-9
  13. Wu W, Wang Q, Li W. Comparison of Tensile and Compressive Properties of Carbon/Glass Interlayer and Intralayer Hybrid Composites. Materials. 2018;11(7):1105. doi:10.3390/ma11071105
  14. Abd El-baky MA. Evaluation of mechanical properties of jute/glass/carbon fibers reinforced hybrid composites. Fibers and Polymers. 2017;18(12):2417-2432. doi:10.1007/s12221-017-7682-x
  15. Abdullah MS, Abdullah AB, Samad Z. Review of hole-making technology for composites. Hole-Making and Drilling Technology for Composites. 2019:1-15. doi:10.1016/b978-0-08-102397-6.00001-5
  16. Meral G, Sarıkaya M, Dilipak H, Şeker U. Multi-response Optimization of Cutting Parameters for Hole Quality in Drilling of AISI 1050 Steel. Arabian Journal for Science and Engineering. 2015;40(12):3709-3722. doi:10.1007/s13369-015-1854-z
  17. Kıvak T, Samtaş G, Çiçek A. Taguchi method based optimisation of drilling parameters in drilling of AISI 316 steel with PVD monolayer and multilayer coated HSS drills. Measurement. 2012;45(6):1547-1557. doi:10.1016/j.measurement.2012.02.022
  18. Meral G, Sarıkaya M, Mia M, Dilipak H, Şeker U. Optimization of hole quality produced by novel drill geometries using the Taguchi S/N approach. The International Journal of Advanced Manufacturing Technology. 2018;101(1-4):339-355. doi:10.1007/s00170-018-2956-z
  19. Shunmugesh K, Panneerselvam K. Optimization of Process Parameters in Micro-Drilling of Carbon Fiber Reinforced Polymer (Cfrp) Using Taguchi and Grey Relational Analysis. Polymers and Polymer Composites. 2016;24(7):499-506. doi:1177/096739111602400708
  20. Babu, J., Paul, L., Ramana, M. V. and Madarapu, A., 2024. Multi-response Optimization while Drilling of Composite Laminate with Core Drill by Grey Entropy Fuzzy (GEF) Method. Mechanics of Advanced Composite Structures, 11(2), pp. 483-502. https://doi.org/10.22075/MACS.2024.31791.1560
  21. Palanikumar, Kayaroganam& B., Latha & Davim, J. Paulo. (2012). Application of Taguchi Method with Grey Fuzzy Logic for the Optimization of Machining Parameters in Machining Composites. Computational Methods for Optimizing Manufacturing Technology: Models and Techniques. 219.
  22. Fedai Y. Optimization of Drilling Parameters in Drilling of MWCNT-Reinforced GFRP Nanocomposites Using Fuzzy AHP-Weighted Taguchi-Based MCDM Methods. Processes. 2023;11(10):2872. doi:10.3390/pr11102872
  23. Bukowski, L., and Feliks, J., “Application of fuzzy sets in evaluation of failure likelihood,” 18th International Conference on Systems Engineering, IEEE, pp. 170-175, Aug. 2005.
  24. Tay, K. M., and Lim, C. P., “Fuzzy FMEA with a guided rules reduction system for prioritization of failures” International Journal of Quality & Reliability Management, vol. 23, no. 8, pp. 1047-1066, 2006.
  25. -S. Chin, A. Chan, and J.-B. Yang, “Development of a fuzzy FMEA based product design system,” International Journal of Advanced Manufacturing Technology, vol. 36, no. 7, pp. 633-649, 2008
  26. -T. Liu and Y.-L. Tsai, “A fuzzy risk assessment approach for occupational hazards in the construction industry,” Safety Science, vol. 50, no.4, pp. 1067-1078, 2012.
  27. Albeanu G and Popentiu-Vladicescu F., “Risk Priority Number Estimation using Intuitionistic-Fuzzy number in Power Engineering,” Journal of Sustainable energy, Vol 6 no 3, pp. 96-101, 2015.
  28. Gupta and R. P. Mishra, “A Failure Mode Effect and Criticality Analysis of Conventional Milling Machine Using Fuzzy Logic: Case Study of RCM,” Quality and Reliability Engineering International, Wiley online library, 2016.
  29. R. Renjith, Manoj Jose kalathil, P. Haresh Kumar and Dilip Madhavan, “Fuzzy FMECA (Failure Mode Effect and Criticality Analysis) of LNG storage facility,” Journal of Loss Prevention in the Process Industries, Vol. 56, pp. 537-547, Nov. 2018.
  30. Gajanand Gupta and Rajesh P. Mishra, “Comparative analysis of traditional and fuzzy FMECA approach for criticality analysis of conventional lathe machine,” Int J Syst Assur Eng Manag, vol. 11(Suppl. 2), pp. 402-411, July 2020.
  31. Dejan V. Petrovi´c, Miloš Tanasijevi´c, Saša Stojadinovi´c, Jelena Ivaz and Pavle Stojkovi, “Fuzzy Model for Risk Assessment of Machinery Failures,” Symmetry, vol. 12, p. 525, 2020.
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