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44 articles for “Fused Deposition Modeling”
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Enhancement of Flexural Strength in FDM-Printed Components through Taguchi-Based Process Parameter Optimization
Abstract: Additive manufacturing (AM), especially Fused Deposition Modeling (FDM), has emerged as a widely adopted and versatile method for producing three-dimensional components. The process involves the deposition of a thermoplastic filament in a semi-molten state, which solidifies in successive layers to form the final structure. While this method enables the production of complex geometries at relatively low cost, the printed parts often exhibit inferior surface quality and reduced mechanical performance compared …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 272–280 Read article
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Design and Performance Evaluation of PLA-based Umbrella Wheels for Stair-Climbing Robotic Applications
Abstract: Staircase climbing robots require a complex design capable of navigating various stair configurations. A crucial component of such robots is the wheel mechanism. This paper focuses on the umbrella wheel mechanism and its application in staircase climbing robots. In this study, a PLA–based umbrella wheel structure is developed and fabricated using fused deposition modeling (FDM) for application in stair-climbing robots. The umbrella wheel geometry enables transformation from a circular rolling …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 808–824 Read article
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Additive Manufacturing of Polymer-Based Advanced Composites: Mechanical Properties and Performance Evaluation
Abstract: Fabrication of large-scale and geometrically complex polymer-based advanced composites via fused deposition modelling (FDM) has been shown to be a promising technology for the production of such materials, however there are challenges in using short carbon fibre-reinforced polylactic acid (CF-PLA) which include obtaining high mechanical performance and maintaining dimensional accuracy with dynamic robot motion and complex interactions occurring between process parameters. The conventional approaches are mostly static feed rates or …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1335 Read article
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Explainable Machine Learning for Process Parameter Optimization in Gradient 3D-Printed Polymer Composites
Abstract: The explainable machine learning-based structure may be employed to achieve a favorable process parameter of the graduate 3D-printed polymer composite structures to improve the mechanical and thermal properties without compromising the transparency of the decisions made during the fabrication process. Gradient composite specimens were made by systematically varied process parameters like nozzle temperature, raster orientation, deposition speed, gradient transition rate and fused filament fabrication. A predictive model of tensile strength …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 847–866 Read article