Optimization of bio-printing process using Design of Experiments (DOE) and Taguchi Method

Maria Veronica Gonzalez Corrales, University of Texas at El Paso

Abstract

At this time there is a need for new fabrication techniques for engineering complex biological structures related to regenerative medicine, in vitro tissue analysis, and pharmaceutical testing with the purpose of placing specific cells in specific target locations. Right now, there is no enough conventional cell seeding methods that can achieve it. In order to achieve it, bio-fabrication, which is a delivery mechanism capable of placing biomaterials, cells, and bioactive macromolecules in specific target locations, comes to play an important role in this area. Among different approaches, bioprinting is one of the most useful processes that use drop-on-demand delivery mechanisms capable of fabricating biological structures. This research presents an experimental study where six factors with two levels each one, are involved in the bioprinting process that are analyzed using the Design of Experiments (DOE) and Taguchi Method in order to find those critical factors that are significant into process that may require some improvements. The six factors with their levels considered in this experiment are: Suspension Method (Medium, PBS), Cartridge Cleaning Method (Pressure, Sonicator), Density (cells/ml) (500K, 1000K), Printer (HP 640C, HP 330), Dot Size (mm2) (3.46, 15.76), and Printing Times (1,5). Furthermore, it is expected to find the optimal operating conditions, that put together can reach the maximum output which in this case is to reach the greatest amount of printed cells. Finally, confirmation runs are conducted to test the accuracy of each approach to determine which method is better. ^

Subject Area

Engineering, Biomedical|Engineering, Industrial

Recommended Citation

Gonzalez Corrales, Maria Veronica, "Optimization of bio-printing process using Design of Experiments (DOE) and Taguchi Method" (2013). ETD Collection for University of Texas, El Paso. AAI1545163.
http://digitalcommons.utep.edu/dissertations/AAI1545163

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