3D Printer parameters analysis for PCL/PLA filament wire using Design of Experiment (DOE)

Abstract

Fabrication of medical implant using composite Polycaprolactone (PCL) / Polylactic Acid (PLA) through a process of fused filament fabrication (FFF) is the future of medical field. In this study the capabilities of FFF process and optimization of the Parameter was investigated to achieve the 20mm × 20mm × 10mm dimensional accuracy of printed composite material. Design of experiment using technique full factorial with two level design is used to study the interaction of factor which is print temperature (A), height of deposition (B), print speed (C) and travel speed (D). By using DOE, the total 20 run include with 4 center point was investigated by extruding the composite material using 3D printer. The dimension accuracy is tested using flexible measuring machine. From the sample, the ANOVA analysis of variance is divided into 3 responses, length, width and height. Factor model A, C and BD show the significant effect on length and for width response, factor model effected the dimensional accuracy is A, C, AC, and AD. Meanwhile for height respond only factor model A and C show the significant effect on the respond. Based on the analysis, one optimum parameter run is selected among ten of the suggested run. The optimum parameter value consists of 136°C print temperature, 0.12mm deposition of height, 20mm/s printing speed and 22mm/s travel speed. The confirmation run analysis this optimum parameter shows the precise dimension with average margin error below that 15% for length, width and height respond.

How generalisable are material extrusion additive manufacturing parameter optimisation studies? A systematic review

“…NGH can also influence the defects listed: Circularity, Cylindricity, Porosity, and Surface Roughness. ↑ [ 10 , 22 , 25 , 32 , 33 , 37 , 46 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 ] ↓ [ 12 , 26 , 27 , 31 , 34 , 35 , 36 , 44 , 45 , 53 , 54 , 62 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , ...…”

“…FVV can also influence the defects listed: Geometrical accuracy, Porosity, and Surface Roughness. ↑ [ 38 , 67 , 71 , 100 , 105 , 113 , 114 ], ↓ [ 73 , 84 , 103 , 115 ] Print head velocity (PHV) Also known as print speed, the velocity the extruder head traversers across the build envelope during deposition and non deposition. PHV can also influence the defects listed: Circularity, Geometrical accuracy, Surface Roughness, Shrinking, and Warping.…”

“…PHV can also influence the defects listed: Circularity, Geometrical accuracy, Surface Roughness, Shrinking, and Warping. ↑ [ 25 , 31 , 37 , 53 , 54 , 61 , 65 , 72 , 73 , 88 , 99 , 100 , 109 , 114 , 116 , 117 ] ↓ [ 32 , 34 , 36 , 68 , 71 , 76 , 92 , 106 , 108 , 112 , 118 ] Air Gap (AG) The measured lateral distance between the centre points of deposited adjacent filament strands. AG can also influence the defects listed: Geometrical accuracy, Porosity, and Surface Roughness.…”

“…ET can also influence the defects listed: Circularity, Geometrical accuracy, Porosity, Surface Roughness, Stringing, and Warping. ↑ [ 28 , 37 , 67 , 73 , 77 , 88 , 105 , 114 , 118 , 123 , 125 , 126 , 127 ] ↓ [ 34 , 36 , 38 , 43 , 54 , 68 , 83 , 90 , 92 , 93 , 95 , 102 , 108 , 111 , 112 , 115 , 116 , 117 , 128 ] Nozzle diameter (ND) The fixed diameter of the nozzle orifice, where the filament is extruded. This directly affects the road width.…”

Determination of optimum production parameters for 3D printers based on nozzle diameter

“…Abdul Haq et al explored parameter optimization using composite PCL/PLA with the FFF process to achieve dimensional accuracy. As a result, the optimum parameters were 136°C printing temperature, 0.12-mm layer thickness, and 20-mm/s printing speed (Abdul Haq et al, 2019). Azhikannickal and Uhrin subjected the material produced with fused deposition modeling (FDM) to rapid heating and cooling.…”