PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

3D printing (3DP) is increasingly utilized to achieve quick turnaround on various geometric designs and prototypes, being the growing part of additive manufacturing technology (AMT). The 3DP technique effectively improves the production of complex models in terms of low-cost, time-consuming production, and with less material volume. The key to results optimisation with 3DP is the preparation of the geometry. The following techniques can effectively reduce the required time of the 3D printing process for complex and non-linear CAD files. The fused deposition modelling/fabrication (FDM/FFF) techniques become the first choice in many applications, including biomedical ones. Still, some obstacles exist in the geometry roughness and quality zones. This paper proposes an optimisation method for 3D printed shapes used in biomedical devices and instrumentation by minimising the support structure attached to the model using the FDM technique. In this research, we proposed a method for dynamic compensation against gravity-affected parts extended from the main object’s geometry using a forward planar learning (FPL) algorithm to minimise cusp height in 3D printed objects. After the slicing stage, the outcomes proved to be of good quality, optimised the object’s surfaces, and minimised the printing time by 32%–38%. The proposed method is promising in defining a better setting for slicing and toolpath for FDM 3D printing. However, this method was not tested on other 3DP methods (Stereolithography (SLA), Selective laser sintering (SLS), and Digital Light Processing (DLP)), as more verification efforts need to be done on these 3D printing processes.

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