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Research Papers

A Unified Strategy to Integrate Information and Methods Across Multiple Training Environments for Assembly Simulations

[+] Author and Article Information
Okjoon Kim

VRCIM Laboratory,
School of Mechanical and Material Engineering,
Washington State University,
Pullman, WA 99164
e-mail: ok.kim@email.wsu.edu

Uma Jayaram

VRCIM Laboratory,
School of Mechanical and Material Engineering,
Washington State University,
Pullman, WA 99164
e-mail: ujayaram@wsu.edu

Lijuan Zhu

VRCIM Laboratory,
School of Mechanical and Material Engineering,
Washington State University,
Pullman, WA 99164
e-mail: zhuliice@wsu.edu

Contributed by the Manufacturing Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received April 28, 2012; final manuscript received February 25, 2014; published online April 28, 2014. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 14(3), 031001 (Apr 28, 2014) (16 pages) Paper No: JCISE-12-1068; doi: 10.1115/1.4027225 History: Received April 28, 2012; Revised February 25, 2014

Training for assembly simulations can be provided using a wide range of technologies from a simple computer-based training (CBT) approach to a complex virtual reality (VR)-based immersive training (IMT) approach. The CBT approach allows user interactions through traditional keyboard and mouse applications, while the IMT approach immerses the user in a virtual environment for a more realistic experience. Typically, for a particular scenario, tools and applications for each of these approaches are developed independently. Consequently, there is much duplication of data and effort, and a lack of synchronization between them. This paper focuses on an integrated approach with support from ontologies to address this problem. Ontologies provide an opportunity to capture and manage common data and map concepts from one application to another in a logical and measured manner. Methods are developed to enable knowledge in these ontologies to be used and shared in a comprehensive and effective manner between CBT and IMT tools. The key contribution of this work is that the ontologies instantiating concepts and properties for the training domain are used effectively among different training tools to deal with common and disparate characteristics between them.

Copyright © 2014 by ASME
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References

Figures

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Fig. 1

iTrain—an approach to increase synchronization and sharing of training models and procedures in a digital training ensemble

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Fig. 7

UML diagram: concept and relationships for SIM-DO, the simulation domain ontology

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Fig. 5

Three-tiered structure of engineering ontologies in product design, assembly simulation, and training domain

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Fig. 4

Knowledge transfer between product design environment and training environment and key ontologies in the iTrain architecture

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Fig. 9

UML diagram: concepts and relationships iTrain-AO

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Fig. 3

Isolation of applications and integration of data by using model-view-controller design pattern

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Fig. 2

Knowledge lifecycle in product design, assembly simulation, and training domain and knowledge sharing between various training tools

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Fig. 6

UML diagram: concepts and relationships for PROE-AO, a product design tool

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Fig. 8

UML diagram: concepts and relationships for TRAIN-DO, the train domain ontology

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Fig. 10

The procedure to instantiate the training ontology

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Fig. 12

Manipulation between the user interfaces and the knowledge models

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Fig. 16

A snapshot for training replacing WFC3 in the Hubble telescope: VCAT on the left and VrToolsPro on the right sharing the geometric models

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Fig. 13

Software structure and libraries of VCAT

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Fig. 11

Population of instances for the simulation domain in the iTrain-AO ontology by using Protégé: a part component's information and its kinematic animation

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Fig. 14

Training models with different train methods and the same train task by instantiating CBT and IMT in Protégé

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Fig. 15

VCAT application importing and displaying training knowledge

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