Literature indicates rapid prototyping (RP) application has become more widespread in design and development of human anatomy models. Practitioners are facing challenges in deployment of RP tools for development of cost-effective medical models, because there are no proven decision support systems in the selection of parameters such as speed, accuracy, materials, and customisation of commercial software. This study aims at alleviating some of these issues by exploring the use of a Genetic Algorithm (GA) approach combined with computer-aided design (CAD) and fused deposition modeling (FDM) techniques. Experiments were conducted using response surface methodology (RSM) to facilitate the optimisation process with build time and model material volume as responses. The validation of the study has been performed with a patella model and the results verified the effectiveness of the proposed RSM-GA approach in the design and development of the anatomical model. The results showed a 27% savings on model material compared to a non-refined model and was deemed satisfactory for practical use as there was a reduction in irregularities from CT data. The study also reveals that the parameter hollow has the largest effect on the responses, followed by the smooth parameter and then the wrap parameter.
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