Automated Knowledge‐Based Design for Additive Manufacturing: A Case Study with Flow Manifolds

Abstract

Additive manufacturing (AM) enables novel process equipment devices. However, the manual 3D design of complex part geometries is frequently challenging as designers need to fulfill functional requirements and consider the restrictions of AM. One promising approach is to automatically generate the design of parts. This work aims to introduce such an automated design approach to practitioners in the area of process engineering. The work describes the basic steps required to develop an automated, knowledge‐based design tool for AM and demonstrates the approach using a case study on flow manifolds.

Knowledge-Driven Design for Additive Manufacturing: A Framework for Design Adaptation

“…The provision and development of DfAM knowledge, tools, rules, processes and methodologies is outlined as one of the most important technical challenges in the field of AM technology (Thompson et al, 2016). This knowledge can thereby be retrieved from use cases, publications, expert interviews, technical documentations and standards (Biedermann et al, 2022). For an efficient use of DfAM, these aforementioned sources need to be formalised, so that in-experienced designers can better explore the potentials and restrictions for designing AM-suitable components and assemblies as they are hardly aware of or do not understand DfAM knowledge and skills (Pradel et al, 2018).…”

“…In this context, a distinction can be made between restrictive rules to ensure manufacturability and functionality as a body of knowledge incorporating information about valid design actions (Jee and Witherell, 2017) and opportunistic guidelines for improving these. Another approach in this field is presented in (Biedermann et al, 2021(Biedermann et al, , 2022. Here, the basic steps for the implementation of an automated design approach combining a knowledge-based approach and the MOKA framework (Methodology and tools Oriented to Knowledge-based engineering Applications) (Consortium, 2001).…”