Joining of Polymer-Metal Hybrid Structures by Fused Deposition Modelling AM Technology

Abstract

Fused deposition modelling (FDM) is one of the most recent advanced joining methods of polymer to metal. This direct joining technology relies on layered material extrusion of the polymer above the surface of the metal to create a permanent connection. FDM joining offers an economical and environmental replacement for conventional joining methods. The strength of the joint between the dissimilar materials is mainly influenced by the metal surface treatment and the extrusion parameters.

This research investigates the joining process of aluminium and Acrylonitrile butadiene styrene (ABS) using FDM, and sheds light on the capabilities of the new joining process. A series of joining experiments were conducted to fabricate single lap joints and study the effect of the printing parameters on the mechanical performance of the joint. The bed temperature, the printing speed, and the nozzle Z offset were varied according to a full factorial design of experiments, and the joint strength was measured using lap joint shear test. The test results were also interpreted through microscopy imaging, material characterization, and thermal analysis. Furthermore, the joining mechanism was investigated, and the contribution of mechanical interlocking and chemical bonding to the joint overall strength was examined.

The results showed that increasing the bed temperature and introducing a nozzle Z offset improved the polymer filling of the aluminium structure. In addition, high printing speed was found to be favourable as it enhanced the interlayer diffusion and preserved the polymer from thermal degradation at elevated bed temperature. The optimized performance of the joint was 2.99±0.04 MPa at a bed temperature of 150°C, printing speed of 60mm/s, and 0.1mm nozzle Z offset. ABS-aluminium joints failure mode was net tension, and mechanical interlocking was the main joining mechanism, but in some cases a (C-O-Al) chemical bond was detected.

Date of Award	Dec 2022
Original language	American English
Supervisor	Jamal Sheikh Ahmad (Supervisor)