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    A Design for Additive Manufacturing Ontology to Support Manufacturability Analysis

    Source: Journal of Computing and Information Science in Engineering:;2019:;volume( 019 ):;issue: 004::page 41014
    Author:
    Kim, Samyeon
    ,
    Rosen, David W.
    ,
    Witherell, Paul
    ,
    Ko, Hyunwoong
    DOI: 10.1115/1.4043531
    Publisher: American Society of Mechanical Engineers (ASME)
    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.
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      A Design for Additive Manufacturing Ontology to Support Manufacturability Analysis

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4257856
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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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    DSpace software copyright © 2002-2015  DuraSpace
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