Multi-Material 3D-Printing Nozzle Design Based on the Theory of Inventive Problem Solving and Knowledge Graph

Abstract

Fused deposition modeling (FDM) technology is an emerging technology with promising applications, with the nozzle playing a crucial role in extrusion, heating, and material ejection. However, most current extrusion-based 3D printers handle only single-material printing, making the integration of multiple materials through a single nozzle challenging due to compromised quality and clogging risks. This paper introduces a method to design multi-material 3D printing nozzles using the Theory of Inventive Problem Solving (TRIZ) and knowledge graph (KG). By optimizing design and leveraging TRIZ’s contradiction resolution principle, this study addressed bottlenecks and complexities in multi-material nozzle design, providing insightful recommendations. A patent knowledge graph focused on spray nozzles was created, storing material properties, design elements, and constraints for enhanced knowledge sharing. Building on identified challenges and recommendations, the study utilized keyword searches and associative paths in the knowledge graph to guide designers in generating innovative solutions. Validation was achieved through two distinct nozzle design models resulting from guided innovations. The TRIZ-KG methodology presented in this paper provides designers with a systematic cognitive framework to empower designers in overcoming technical obstacles and proposing precise solutions.

Keywords

• multi-material 3D-printing nozzle
• Theory of Inventive Problem Solving (TRIZ)
• knowledge graph (KG)
• inventive principle
• nondestructive testing
• structural health monitoring