Greener 3D Printing: The Role of Artificial Intelligence in Sustainable Polymer and Composite Manufacturing

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Year : 2026 | Volume : 14 | 01 | Page :
    By

    J. Surendra,

  • K. Durga Hemanth Kumar,

  • J.Ranga Raya Chowdary,

  • M. Vijaya,

  • B. Harish Babu,

  1. Assistant Professor, Department of Mechanical Engineering, Prasad V Potluri Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India
  2. Assistant Professor, Department of Mechanical Engineering, Sagi Rama Krishnam Raju Engineering College (A), China Amiram, Bhimavaram, Andhra Pradesh, India
  3. Assistant Professor, Department of Mechanical Engineering, R.V.R&J.C College of Engineering, Chowdavaram, Guntur, Andhra Pradesh, India
  4. Associate Professor, Department of Mechanical Engineering , R.V.R&J.C College of Engineering, Chowdavaram, Guntur, Andhra Pradesh, India
  5. Assistant Professor, Department of Automobile Engineering, VNR Vignana Jyothi institute of Engineering and Technology, Hyderabad, Telangana, India

Abstract

The integration of sustainable materials with additive manufacturing (AM) technologies marks a significant step toward environmentally responsible production. Biodegradable polymers, recycled thermoplastics, and bio-based composites, when used in 3D printing, offer the potential to reduce the ecological footprint of manufacturing. However, optimizing the interplay between material properties, process parameters, and product performance remains a complex challenge. This review examines how artificial intelligence (AI) is being applied to address these challenges and improve the efficiency and sustainability of 3D printing using eco-friendly polymers and polymer matrix composites. It highlights a range of AI techniques—including machine learning (ML), deep learning (DL), reinforcement learning (RL), and hybrid metaheuristic models—used for tasks such as parameter optimization, defect detection, quality control, and performance prediction. The study categorizes current research based on sustainable material types (e.g., PLA, PHA, recycled PET, natural fiber-reinforced composites), AI algorithms used, and targeted optimization objectives, such as mechanical strength, energy efficiency, and waste reduction. It also explores key limitations, including data scarcity, model interpretability, and the difficulty of generalizing results across different materials and printing platforms. Finally, the review outlines future directions, calling for open datasets, explainable AI models, integration with life cycle assessment (LCA), and multi-objective optimization strategies that balance performance, sustainability, and cost. Overall, the paper underscores AI’s crucial role in advancing greener, smarter, and more efficient additive manufacturing systems.

Keywords: 3D printing, Polymers, Artificial intelligence, PLA, PHA.

How to cite this article:
J. Surendra, K. Durga Hemanth Kumar, J.Ranga Raya Chowdary, M. Vijaya, B. Harish Babu. Greener 3D Printing: The Role of Artificial Intelligence in Sustainable Polymer and Composite Manufacturing. Journal of Polymer & Composites. 2026; 14(01):-.
How to cite this URL:
J. Surendra, K. Durga Hemanth Kumar, J.Ranga Raya Chowdary, M. Vijaya, B. Harish Babu. Greener 3D Printing: The Role of Artificial Intelligence in Sustainable Polymer and Composite Manufacturing. Journal of Polymer & Composites. 2026; 14(01):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=236323


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Ahead of Print Subscription Review Article
Volume 14
01
Received 07/10/2025
Accepted 15/11/2025
Published 27/01/2026
Publication Time 112 Days
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