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2024-10-15
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Original Research Article
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Copyright (c) 2024 Subramani Raja, Rusho Maher Ali, Yogita V. Babar, Raviteja Surakasi, S. Karthikeyan, Bhuvaneswari Panneerselvam, A. S. Jagadheeswari
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How to Cite
Integration of nanomaterials in FDM for enhanced surface properties: Optimized manufacturing approaches
Subramani Raja
Centre for Sustainable Materials and Surface, Metamorphosis, Chennai Institute of Technology Chennai, India
Rusho Maher Ali
Lockheed Martin Engineering Management, University of Colorado, Boulder, Colorado, 80308, United States
Yogita V. Babar
Institute-Sanjay Ghodawat University Kolhapur & KBPCOE Satara, Maharashtra, 416012, India
Raviteja Surakasi
Department of Mechanical Engineering, Lendi Institute of Engineering and Technology, Jonnada, Vizianagaram Andhra Pradesh, 535005, India
S. Karthikeyan
Department of Mechanical Engineering, Erode Sengunthar Engineering College, Erode, Tamilnadu, 638057, India
Bhuvaneswari Panneerselvam
Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, Tamilnadu, 600062, India
A. S. Jagadheeswari
Department of Civil Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamilnadu, 642109, India
DOI: https://doi.org/10.59429/ace.v7i3.5534
Abstract
This article presents a comprehensive review of advanced techniques for integrating nanomaterials into fused deposition modeling (FDM) processes, addressing prevalent challenges such as limited surface quality and wear resistance in traditional FDM-printed parts. The integration of nanomaterials offers potential solutions to these issues by enhancing surface properties. This review explores key methodologies, including direct nanoparticle mixing with polymer filaments, in-situ polymerization, and surface coating techniques, and demonstrates their impact on improving surface roughness and wear resistance. Specifically, nanomaterial-enhanced composites achieve up to a 30% reduction in surface roughness and a 40% improvement in wear resistance compared to conventional materials. To optimize manufacturing processes, we apply the Taguchi method to identify critical process parameters such as extrusion temperature, print speed, layer thickness, and nanoparticle concentration that influence surface properties. Our simulations and analysis of variance (ANOVA) indicate that optimal settings can enhance surface quality by 25% and improve wear resistance by 35%. The proposed methodologies and theoretical framework lay the groundwork for experimental validation, which will involve testing the optimized parameters and assessing their practical impact. This research advances the field of additive manufacturing by providing novel insights into nanomaterial integration, paving the way for improved FDM technology with applications spanning aerospace, biomedical engineering, and beyond. The findings contribute significantly to overcoming existing limitations and enhancing the performance of FDM-printed parts.
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