Experimental Investigation of FDM-Based 3D Printed Components Using Multi-Criteria Decision-Making Techniques

Additive Manufacturing (AM), particularly Fused Deposition Modelling (FDM), has emerged as a versatile fabrication technology capable of producing complex geometries with reduced material waste and lead time. However, the performance of FDM-fabricated parts is highly dependent on build orientation, material selection, and process parameters, which often involve conflicting objectives such as build time, material consumption, cost, and surface quality. This study presents a systematic experimental investigation of 3D printed polymer components using integrated Multi-Criteria Decision-Making (MCDM) techniques. Analytic Hierarchy Process (AHP) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) are employed to evaluate and rank different build orientations for PLA and ABS materials fabricated using an FDM printer. Quantitative criteria including build time, material usage, part weight, and filament length are combined with qualitative decision preferences to identify the optimal orientation. Experimental results reveal that PLA printed in Position-2 consistently outperforms other alternatives, demonstrating superior efficiency across both AHP and MOORA methods. The study confirms that integrated MCDM approaches offer a robust framework for optimizing additive manufacturing decisions and improving process planning reliability.