Vol. 8 No. 4(Publishing) | Applied Chemical Engineering

Vol. 8 No. 4(Publishing)

Table of Contents

Open Access
Original Research Article
by Hayjaa Mohaisen Mousa, Ala’a D. Noor, Haider Falih Shamikh Al-Saedi, Shahlaa Majid J., Jaber Hameed Hussain, Mohannad Mohammed, Israa Alhani, Baraa G. Alani
2025,8(4);    109 Views
Abstract The global shift toward sustainable manufacturing has intensified interest in eco-friendly materials and optimized processing strategies for additive manufacturing technologies such as Fused Deposition Modeling (FDM). Polylactic acid (PLA)-based green composites have emerged as promising candidates due to their biodegradability, low environmental impact, and compatibility with FDM systems. However, the optimization of FDM process parameters for such composites remains a significant challenge due to the inherent trade-offs between mechanical performance, energy consumption, and material sustainability. This study addresses this gap by employing an integrated multi-criteria decision-making (MCDM) framework—Fuzzy Analytic Hierarchy Process (Fuzzy AHP) combined with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)—to identify optimal FDM parameter settings for PLA-based green composites. Key process parameters, including layer thickness, print speed, infill density, and nozzle temperature, are evaluated against performance criteria such as tensile strength, surface finish, material utilization, and energy efficiency. Literature reports suggest optimal ranges such as 0.1–0.2 mm for layer thickness, 40–60 mm/s for print speed, and 80–100% for infill density to enhance part strength and minimize waste. The Fuzzy AHP–TOPSIS approach enables robust decision-making under uncertainty, providing a sustainable design methodology aligned with SDGs 4 (Quality Education), 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure), and 12 (Responsible Consumption and Production). This study establishes a foundational framework for future experimental validation and promotes informed parameter selection for sustainable, high-performance FDM manufacturing of PLA-based green composites.
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