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Additive manufacturing through three-dimensional (3D) and four-dimensional (4D) printing has transformed modern production with improved design flexibility, efficiency, and material utilization. Despite these advantages, the selection and prioritization of process parameters remains a complex challenge. This study employs the Fuzzy Analytical Hierarchy Process (FAHP) to systematically evaluate expert survey data on parameters such as tool path setting, print speed, extrusion temperature, material choice, bed temperature, support removal, surface finishing, and time–cost considerations. Using pairwise comparison matrices converted into triangular fuzzy numbers (TFNs), the FAHP framework calculates fuzzy weights, applies de-fuzzification, and normalizes the results to derive parameter priorities. The findings reveal that Extrusion Temperature and Bed Temperature are critical for 4D printing, whereas Surface Finishing and Support Removal dominate in 3D printing. This highlights the shift in the significance of the parameters between the two technologies. Additionally, the FAHP-based desirability index supports the justification of 4D printing applications, particularly in mechatronics and the Internet of Things, offering valuable optimization insights for researchers and industry. The novelty of the study lies in establishing an FAHP-based decision framework that prioritizes eight printing and post-processing criteria and compares 3D and 4D printing at the technology level for IoT and mechatronic applications under uncertain expert judgments.
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Kumari et al. (2026) studied this question.
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