Development of a fuzzy‐AHP system to select the printing method for polycaprolactone (PCL)‐based scaffolds

Abstract

Polycaprolactone (PCL)-based scaffolds have great potential in various tissue engineering applications because of their biodegradability, high mechanical strength, and easy fabrication using different 3D printing methods. However, previous research has only focused on developing and examining each PCL-based scaffold printing method’s merits and limitations separately. Thus, the lack of a systematic comparison of the various methods to recommend the most appropriate one for each application remains. This paper provides an overview of different PCL-based scaffold printing methods. Four typical 3D printing methods for fabricating PCL-based scaffolds and five important evaluation criteria including quality, usage, productivity, cost, and flexibility are identified. The integrated fuzzy-analytical hierarchy process (i-FAHP) and sensitivity analysis are proposed as multi-criteria decision-making methods for selecting the most appropriate scaffold printing method (SPM) under constrained construction and material types. Customized software based on a flexible fuzzy-AHP expert system is built to support decision-makers in determining the optimal SPM quickly and effectively. The result shows that the melt-based extrusion method is optimal for different scaffold types. This study’s findings will be useful for developing biomaterials and multi-head 3D bioprinters for customized and commercial tissue engineering applications.