Selecting the most suitable 3D printing technology for custom manufacturing using fuzzy decision-making methodology

Abstract

The rapid advancements in 3D printing technologies have significantly reshaped the manufacturing landscape, enabling highly customized and efficient production processes. However, selecting the most appropriate 3D printing technology for custom manufacturing is a complex decision that requires careful consideration of multiple, often conflicting criteria. Addressing this challenge, this study introduces a novel Fermatean fuzzy multi-criteria decision-making (MCDM) framework to facilitate informed technology selection. The proposed methodology combines the Best-Worst Method for weighting criteria with the Fermatean Fuzzy Weighted Aggregated Sum Product Assessment (FF-WASPAS) method for ranking alternatives, marking the first application of this hybrid approach in the literature. To demonstrate the framework, six leading 3D printing technologies were evaluated across nine critical criteria: Cost, Precision and Surface Quality, Finishing Requirement, Production Speed, Material Compatibility, Functional Durability, Ability to Manufacture Complex Geometry, Environmental Impact, and Technological Maturity. The analysis identified Stereolithography (SLA) as the best alternative for custom manufacturing, with the most critical criteria being Precision and Surface Quality, Functional Durability, and Ability to Manufacture Complex Geometry. This study offers a systematic and robust decision-making framework, providing valuable guidance for manufacturing authorities in selecting the most suitable 3D printing technology for customized applications.