A 3d-printing knowledge base for early phase product engineering decisions

R. Willmann
Carinthia University of Applied Sciences,
Austria

Keywords: additive manufacturing, knowledge base, engineering support, design pattern

Summary:

3D printing is an emerging production technique nowadays also reaching out for small volume production. The degrees of freedom make it superior to other manufacturing processes under particular circumstances. Achievable complexity of design, the variation of material characteristics inside objects or the integration of multiple functions in one single part are just a few examples. However, applying such degrees of freedom already during the engineering phase of new products requires extensive knowledge about capabilities of different 3D-printing methods. A recommender system, integrated with state of the art design tools, shall provide such knowledge to mechanical engineers during the phase of product engineering. The proposed paper introduces an iterative process combining the classical engineering process with a decision-making system based on elements of axiomatic design, innovative problem solving (TIPS) and design patterns for 3D printing. Starting from design decisions based on functional requirements, the underlying knowledge base immediately provides applicable design patterns, and how they can be adapted in the respective problem case. Moreover, it proposes potential 3D printing techniques and how to consider their opportunities and constraints in a product's design (Fig. 1 of attachment) . The knowledge base is structured by triples (triple store) providing the semantic association between contradictions and innovation principles of TRIZ, as well as between innovation principles and design patterns attached with case studies and 3D printing techniques. The 3D printing-community can adopt and enhance this knowledge base, as the schema of the knowledge base shall be made publicly available. Consequently, it is possible for mechanical engineers to adopt technical approaches of 3D-printing easier. Secondly, this approach provides a supporting source for potential applications of 3d-printing during innovation processes in research and innovation teams.