Enhancing shear strength in 3D printed single lap composite joints: A multi‐faceted exploration of GNP integration, print orientation, utilizing artificial neural networks, and dynamic analysis

Abstract The state‐of‐the‐art manufacturing process known as additive manufacturing (AM) employs components that may be processed by AM, including ceramics, polymeric materials, metallic substances, titanium, metallic substances, and composites, to produce parts with intricate designs and exact properties. Fused deposition modeling (FDM) is a rapidly growing 3D printing technique. However, most FDM systems only support polylactic acid (PLA) or acrylonitrile butadiene styrene (ABS) as a printing medium. The impact of print orientations and graphene nanoparticles upon the tensile and shear properties of PLA single‐lap joint samples created by FDM has been investigated in this work. According to experimentation, the 0° orientation has the highest load‐bearing capacity and shear strength compared to 45° and 90°. Also, addition of GNP to epoxy adhesive improved greatly, with 0.25 to 1.00 weight percentages of 20.94, 12.34, 38.98, and 31.11%, respectively. FESEM has been used to analyze the failure criteria. The free vibrational analysis confirmed that the 3DS6 sample had the highest natural frequency (598.7 Hz) compared to all other samples. The artificial neural network (ANN) approach accurately predicted the failure load. The overall =0.8471 achieved is below the permissible margin of error, indicating that both the outcomes are reliable and in satisfactory agreement.