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research-article

A Design for Additive Manufacturing Ontology to Support Manufacturability Analysis

[+] Author and Article Information
Samyeon Kim

8 Somapah Road singapore, Singapore 487372 Singapore samyeon_kim@sutd.edu.sg

David W. Rosen

813, Ferst Drive School of Mechanical Engineering Atlanta, GA 30332 david.rosen@me.gatech.edu

Paul Witherell

Engineering Laboratory Life Cycle Engineering Group Gaithersburg, MD 20899 paul.witherell@nist.gov

Hyunwoong Ko

100 Bureau Drive Gaithersburg, MD 20899 hyunwoong.ko@nist.gov

1Corresponding author.

Manuscript received December 11, 2018; final manuscript received March 26, 2019; published online xx xx, xxxx. Assoc. Editor: Charlie C.L. Wang.

*He is also with School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798.

ASME doi:10.1115/1.4043531 History: Received December 11, 2018; Accepted March 27, 2019

Abstract

Design for additive manufacturing (DFAM) provides design freedom for creating complex geometries and guides designers to ensure the manufacturability of parts fabricated using additive manufacturing (AM) processes. However, there is a lack of formalized DFAM knowledge that provides information on how to design parts and how to plan AM processes for achieving target goals. Furthermore, the wide variety of AM processes, materials, and machines creates challenges in determining manufacturability constraints. Therefore, this study presents a DFAM ontology using the web ontology language (OWL) to semantically model DFAM knowledge and retrieve that knowledge. The goal of the proposed DFAM ontology is to provide a structure for information on part design, AM processes, and AM capability to represent design rules. Furthermore, the manufacturing feature concept is introduced to indicate design features that are considerably constrained by given AM processes. After developing the DFAM ontology, queries based on design rules are represented to explicitly retrieve DFAM knowledge and analyze manufacturability using Semantic Query-enhanced Web Rule Language (SQWRL). The SQWRL rules enable effective reasoning to evaluate design features against manufacturing constraints. The usefulness of the DFAM ontology is demonstrated in a case study where design features of a bracket are selected as manufacturing features based on a rule development process. This study contributes to developing a reusable and upgradable knowledge base that can be used to perform manufacturing analysis.

Copyright © 2019 by ASME
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