Optimizing the printing parameters for dimensional accuracy of distal femur bone by using Taguchi’s method

Abstract

Background: Fused deposition modelling (FDM) is a popular additive manufacturing technique with capability of producing complex and integrate shapes. One of the critical aspects of FDM is the dimensional accuracy of 3D (three-dimension) printed model, especially in medical science applications, as proper fit and function with human body can prevent patient’s discomfort, complication or even harm. Objective: In this research work, the optimisation of print parameters: layer height, nozzle temperature, printing speed, infill pattern and infill density for improving the dimensional accuracy of distal femur bone, an irregular and complex shaped geometry is carried out using Taguchi’s method and to study its influence using ANOVA (analysis of variance). Methodology: 3D CAD (computer-aided design) model of the distal femur bone is generated from a CT (computerized tomography) scan using 3D slicer and its associated errors are corrected using Ansys SpaceClaim. The model is prepared for printing using Ultimaker Cura as per L16 orthogonal array experimental layout where TEA (trans epicondylar axis), which is the distance between the most prominent point of the lateral and medial epicondyle, is set at 45° from X-axis in XY plane, i.e. diagonally on the plane of printing bed. It is then printed with PLA (polylactic acid) filament. Length along TEA is compared accordingly with 3D CAD model. Taguchi’s method of ‘smaller the better’ is applied for reducing deviation. Further, ANOVA analysis is done on the data set and a linear regression model is also developed. Result: Through Taguchi’s method, the optimum parameters were found to be triangle for infill pattern, 200 °C for nozzle temperature, 30 mm/s for nozzle speed, 0.1 mm for layer height and 40% for infill density. ANOVA analysis shows that all parameters contribute significantly with layer height being the most influential parameter, followed by infill pattern, nozzle speed, nozzle temperature and infill density. Mathematical model through multiple linear regression method was developed with determination of coefficient value of 96.91% and standard residual value is within the acceptable range of ± 2 indicating that there is no outliner in the data.