4.6 Article

Nondeterministic multiobjective optimization of 3D printed ceramic tissue scaffolds

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DOI: 10.1016/j.jmbbm.2022.105580

Keywords

Tissue scaffold; Additive manufacturing; Nondeterministic design; Multiobjective robust optimization; Bioceramics; Uncertainty; Direct ink writing (robocasting)

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Despite advances in bone scaffold design optimization, their functionality remains suboptimal due to uncertainties caused by the manufacturing process. A novel multi-objective robust optimization approach is proposed to minimize the effects of uncertainties on the optimized design. This study presents the first non-deterministic optimization of tissue scaffold, shedding light on the significant topic of scaffold design and additive manufacturing.
Despite significant advances in the design optimization of bone scaffolds for enhancing their biomechanical properties, the functionality of these synthetic constructs remains suboptimal. One of the main challenges in the structural optimization of bone scaffolds is associated with the large uncertainties caused by the manufacturing process, such as variations in scaffolds' geometric features and constitutive material properties after fabrication. Unfortunately, such non-deterministic issues have not been considered in the existing optimization frameworks, thereby limiting their reliability. To address this challenge, a novel multiobjective robust optimization approach is proposed here such that the effects of uncertainties on the optimized design can be minimized. This study first conducted computational analyses of a parameterized ceramic scaffold model to determine its effective modulus, structural strength, and permeability. Then, surrogate models were constructed to formulate explicit mathe-matical relationships between the geometrical parameters (design variables) and mechanical and fluidic prop-erties. The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) was adopted to generate the robust Pareto solutions for an optimal set of trade-offs between the competing objective functions while ensuring the effects of the noise parameters to be minimal. Note that the nondeterministic optimization of tissue scaffold presented here is the first of its kind in open literature, which is expected to shed some light on this significant topic of scaffold design and additive manufacturing in a more realistic way.

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