Enhancing Mechanical Properties by Parameter Optimization in Fiber and Particle Reinforced Composites

Year : 2025 | Volume : 13 | Issue : 02 | Page : 75 85
    By

    Shikalgar Niyaj Dilavar,

  • Ashwin Sailesh,

  • Manas Ranjan Sahoo,

  • DVSSSV Prasad,

  • K. Suresh Kumar,

  • M Vamsi Krishna,

  • R. Anandkumar,

  • Murali. D,

  • G. Nalinashini,

  1. Associate Professor, Department of Automation and Robotics, Dr D Y Patil Institute of Technology, Pune, Maharashtra, India
  2. Assistant Professor, Department of Mechanical Engineering, Sri Sairam Institute of Technology, Chennai, Tamil Nadu, India
  3. Assistant Professor, Department of Mechanical Engineering, Srinix College of Engineering, Balasore, Odisha, India
  4. Professor, Department of Mechanical Engineering, Aditya University, Surampalem, Andhra Pradesh, India
  5. Associate Professor, Department of Mechanical Engineering, K.S.R.M. College of Engineering, Kadapa, Andhra Pradesh, India
  6. Professor, Department of Sri Venkateswara College of Engineering Tirupathi, Andhra Pradesh, India
  7. Assistant Professor, Department of Mechanical Engineering, KPR Institute of Engineering and Technology, Tamil Nadu, India
  8. Assistant Professor, Department of Mechanical Engineering, St. Joseph’s Institute of Technology, Chennai, Tamil Nadu, India
  9. Professor, Department of Electronics and Communication Engineering, Dr. M.G.R. Educational and Research Institute, Chennai, Tamil Nadu, India

Abstract

This research focuses on optimizing the mechanical and thermal properties of hybrid fiber and particle-reinforced composites through systematic parameter optimization using the Taguchi method and Grey Relational Analysis (GRA). Composites were fabricated using varying fiber volume fractions (20%, 30%, and 40%), particle sizes (20 μm, 60 μm, and 100 μm), and curing temperatures (60°C, 80°C, and 100°C) in a 3-factor, 3-level experimental design. Key properties such as tensile strength, impact resistance, and thermal stability were evaluated, with optimization guided by signal-to-noise (S/N) ratios and GRA. The optimal combination was identified as 30% fiber volume fraction, 60 μm particle size, and 100°C curing temperature, achieving superior performance metrics: tensile strength of 290 MPa, impact resistance of 55 J/m, and thermal stability of 340°C.Compared to suboptimal settings, the optimized parameters led to a 15-20% enhancement in tensile strength, a 22% increase in impact resistance, and a significant boost in thermal stability, attributed to improved fiber-matrix bonding, uniform particle dispersion, and effective cross-linking during curing. The study demonstrated that higher fiber content improved reinforcement but required balance to avoid brittleness, while intermediate particle sizes ensured stress distribution without agglomeration. The curing temperature was pivotal, with 100°C achieving maximum cross-linking without risking thermal degradation. This work underscores the effectiveness of combining experimental design and GRA in tailoring composites for advanced engineering applications, offering a replicable framework for future optimization studies.

Keywords: Fiber reinforced composites, parameter optimization, mechanical properties, grey relational analysis, thermal stability.

[This article belongs to Journal of Polymer and Composites ]

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How to cite this article:
Shikalgar Niyaj Dilavar, Ashwin Sailesh, Manas Ranjan Sahoo, DVSSSV Prasad, K. Suresh Kumar, M Vamsi Krishna, R. Anandkumar, Murali. D, G. Nalinashini. Enhancing Mechanical Properties by Parameter Optimization in Fiber and Particle Reinforced Composites. Journal of Polymer and Composites. 2025; 13(02):75-85.
How to cite this URL:
Shikalgar Niyaj Dilavar, Ashwin Sailesh, Manas Ranjan Sahoo, DVSSSV Prasad, K. Suresh Kumar, M Vamsi Krishna, R. Anandkumar, Murali. D, G. Nalinashini. Enhancing Mechanical Properties by Parameter Optimization in Fiber and Particle Reinforced Composites. Journal of Polymer and Composites. 2025; 13(02):75-85. Available from: https://journals.stmjournals.com/jopc/article=2025/view=198137


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Regular Issue Subscription Original Research
Volume 13
Issue 02
Received 09/12/2024
Accepted 10/01/2025
Published 24/01/2025
Publication Time 46 Days
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