Bokus
Senthilkumar Krishnasamy, Chandrasekar Muthukumar, Senthil Muthu Kumar Thiagamani, Siva Irulappasamy - Additive Manufacturing of Natural Fiber-Based Composites, Häftad

Häftad, Engelska, 2027

Additive Manufacturing of Natural Fiber-Based Composites

Av Senthilkumar Krishnasamy, Chandrasekar Muthukumar, Senthil Muthu Kumar Thiagamani, Siva Irulappasamy

2830 kr

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Beskrivning
Additive Manufacturing of Natural Fiber-Based Composites delivers a comprehensive exploration of integrating natural fibers into a variety of 3D printing (additive manufacturing) techniques, including Fused Deposition Modeling (FDM), Stereolithography (SLA), Selective Laser Sintering (SLS), and binder jetting. The book’s primary objective is to raise awareness of sustainable materials among students, researchers, and industrial professionals by examining the environmental benefits, technical challenges, and recent advances in the use of natural fiber composites. The book addresses the limitations of natural fibers, such as their hydrophilic nature, and offers detailed solutions including surface treatments, improved fiber dispersion, and enhanced matrix compatibility. It highlights emerging trends, such as the application of machine learning in predicting material properties and optimizing 3D printing processes and provides strategies to overcome key technical obstacles. Structured into four sections-covering fundamentals, materials and processes, applications and trends, and comparative studies, the book offers modular chapters that are practical for both academic and industrial audiences. The book’s timely focus on eco-friendly, recyclable composites and its inclusion of machine learning applications uniquely positions it as a forward-looking resource, supporting the transition to sustainable manufacturing and addressing pressing global needs for green innovation.

  • Comprehensive coverage of natural fiber composites in additive manufacturing
  • Emphasis on environmental impact and sustainability
  • Contains expanded case studies covering different AM techniques (e.g., DIW, BJ, SLS, FDM)
  • Integration of machine learning and predictive modeling for advanced material optimization
  • Real-world applications and industry-relevant solutions in various matrices (polymers, ceramics, metals)
  • Extended focus on processability, fiber-matrix compatibility, and troubleshooting
  • Covers economics, longevity/resilience, and distributed manufacturing
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