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contributor authorKim, Samyeon
contributor authorRosen, David W.
contributor authorWitherell, Paul
contributor authorKo, Hyunwoong
date accessioned2019-09-18T09:00:43Z
date available2019-09-18T09:00:43Z
date copyright6/13/2019 12:00:00 AM
date issued2019
identifier issn1530-9827
identifier otherjcise_19_4_041014
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4257856
description abstractDesign 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.
publisherAmerican Society of Mechanical Engineers (ASME)
titleA Design for Additive Manufacturing Ontology to Support Manufacturability Analysis
typeJournal Paper
journal volume19
journal issue4
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.4043531
journal fristpage41014
journal lastpage041014-10
treeJournal of Computing and Information Science in Engineering:;2019:;volume( 019 ):;issue: 004
contenttypeFulltext


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