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Research Papers

A Knowledge-Based Method for Innovative Design for Additive Manufacturing Supported by Modular Ontologies

[+] Author and Article Information
Thomas J. Hagedorn

Mem. ASME
Mechanical and Industrial Engineering,
UMass Amherst,
Amherst, MA 01003
e-mail: thagedorn@umass.edu

Sundar Krishnamurty

Fellow ASME
Mechanical and Industrial Engineering,
UMass Amherst,
Amherst, MA 01003
e-mail: skrishna@umass.edu

Ian R. Grosse

Fellow ASME
Mechanical and Industrial Engineering,
UMass Amherst,
Amherst, MA 01003
e-mail: grosse@umass.edu

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received November 15, 2017; final manuscript received February 17, 2018; published online March 19, 2018. Assoc. Editor: Ying Liu.

J. Comput. Inf. Sci. Eng 18(2), 021009 (Mar 19, 2018) (12 pages) Paper No: JCISE-17-1272; doi: 10.1115/1.4039455 History: Received November 15, 2017; Revised February 17, 2018

Additive manufacturing (AM) offers significant opportunities for product innovation in many fields provided that designers are able to recognize the potential values of AM in a given product development process. However, this may be challenging for design teams without substantial experience with the technology. Design inspiration based on past successful applications of AM may facilitate application of AM even in relatively inexperienced teams. While designs for additive manufacturing (DFAM) methods have experimented with reuse of past knowledge, they may not be sufficient to fully realize AM's innovative potential. In many instances, relevant knowledge may be hard to find, lack context, or simply unavailable. This design information is also typically divorced from the underlying logic of a products' business case. In this paper, we present a knowledge based method for AM design ideation as well as the development of a suite of modular, highly formal ontologies to capture information about innovative uses of AM. This underlying information model, the innovative capabilities of additive manufacturing (ICAM) ontology, aims to facilitate innovative use of AM by connecting a repository of a business and technical knowledge relating to past AM products with a collection of knowledge bases detailing the capabilities of various AM processes and machines. Two case studies are used to explore how this linked knowledge can be queried in the context of a new design problem to identify highly relevant examples of existing products that leveraged AM capabilities to solve similar design problems.

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Figures

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Fig. 1

Partial representation of BFO class structure. Arrows represent a subclass relation between boxes.

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Fig. 7

Proposed process for design ideation using ICAM

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Fig. 3

Dependency relations among modular ontologies

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Fig. 2

High-level schematic of the implementation of the ICAM ontology

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Fig. 8

Representation of folding surgical tool model in ICAM. The tool is inserted in a folded configuration, then unfolds in vivo. Model based on device reported in Ref. [58].

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Fig. 9

Representation of case in ICAM. The tool undergoes significant deformation during introduction. However, it is made of a shape memory material, which changes shape in vivo to block a vessel. From Ref. [59].

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Fig. 6

Partial class hierarchy depicting AM capabilities identified during the literature review

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Fig. 5

Additive manufacturing machinery role in value delivery model in the BEM ontology

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Fig. 4

Partial representation of the information model implemented in the proposed BEM

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Fig. 10

Concept generated from queries of ICAM: (a) folding box structure that uses a hinge to fold and (b) base unit of endocutter stapling surface. Black rectangles represent wells containing staples. The individual segments fold over on another as the box itself folds, advancing the center rows.

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