Tissue engineering using three-dimensional porous scaffolds has shown promise for the restoration of normal function in injured and diseased tissues and organs. Rigorous control over scaffold architecture in melt extrusion additive manufacturing is highly restricted mainly due to pronounced variations in the deposited strand diameter upon any variations in process conditions and polymer viscoelasticity. We have designed an I-optimal, split-plot experiment to study the extrudate swell in melt extrusion additive manufacturing and to control the scaffold architecture. The designed experiment was used to generate data to relate three responses (swell, density, and modulus) to a set of controllable factors (plotting needle diameter, temperature, pressure, and the dispensing speed). The fitted regression relationships were used to optimize the three responses simultaneously. The swell response was constrained to be close to 1 while maximizing the modulus and minimizing the density. Constraining the extrudate swell to 1 generates design-driven scaffolds, with strand diameters equal to the plotting needle diameter, and allows a greater control over scaffold pore size. Hence, the modulus of the scaffolds can be fully controlled by adjusting the in-plane distance between the deposited strands. To the extent of the model’s validity, we can eliminate the effect of extrudate swell in designing these scaffolds, while targeting a range of porosity and modulus appropriate for bone tissue engineering. The result of this optimization was a predicted modulus of 14 MPa and a predicted density of 0.29 g/cm3 (porosity ≈ 75%) using polycaprolactone as scaffold material. These predicted responses corresponded to factor levels of 0.6 μm for the plotting needle diameter, plotting pressure of 2.5 bar, melt temperature of 113.5 °C, and dispensing speed of 2 mm/s. The validation scaffold enabled us to quantify the percentage difference for the predictions, which was 9.5% for the extrudate swell, 19% for the density, and 29% for the modulus.
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