View updates and constraint validations in collaborative design environments

Yoo, Sang Bong; Kim, Ki-Chang; Yoo, Hyeong Seon

doi:10.1177/1063293x11435345

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…Consistency of interfaces among component parts should be checked by the owner of the higher level node. As explained in Yoo et al (2012) and Yoo and Suh (1999), such consistency can be automatically verified by including logical constraints. The proposed method is independent of modeling methodologies such as surface model and feature-based parametric model.…”

Section: Resultsmentioning

confidence: 99%

Collaborative design by sharing multiple-level encryption files

Kim

Yoo

2013

Concurrent Engineering

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A design file can grow in size as the complexity of the target object increases. A large design file can reside in a large parallel computing system, such as a cloud computing system, and many designers can work concurrently on the same file. In such a case, it is obvious that we need some kind of protection mechanism allowing each user to access only the area of the file they are permitted to access. We take the encryption approach to ensure the safety of a file, even in the public domain such as on a cloud system, and in this article, we suggest a multi-level encryption scheme allowing each user to access a file only at the level the user has legitimate right to access. Each level of the file is encrypted with a different key, and the keys are shown only to those who have the right access permission. This article describes the necessary file format used to achieve this goal and discusses the file manipulation functions used to handle this new file format.

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Section: Resultsmentioning

confidence: 99%

Collaborative design by sharing multiple-level encryption files

Kim

Yoo

2013

Concurrent Engineering

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“…Collaborative design is considered as a promising business strategy in addressing global competition (Chen et al, 2008; Li et al, 2009; Tseng and Abdalla, 2006). A crucial factor for collaborative design lies in the ability to exchange information among multiple domains in a distributed, heterogeneous, and dynamic environment (Ai et al, 2010; Demoly et al, 2012; Šormaz et al, 2010; Yoo et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Ontology-based information integration and sharing for collaborative part and tooling development

He¹,

Ming²,

Ni³

et al. 2015

Concurrent Engineering

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One critical factor in collaborative part and tooling development is the information integration and sharing. After analyzing characteristics of the collaboration process, the problem of information integration and sharing is transformed into a problem of domain ontology integration and sharing. First, an activity model is presented to describe interactions among domains of part, process, and tooling. Next, three local ontologies are constructed to serve as formal, explicit specifications of domain-specific information. To integrate local ontologies as global ontology, the relations and constrains among domains are explicitly represented using Semantic Web Rule Language. Then, the ontology sharing method via similarity matching is studied. Finally, the proposed approach is demonstrated by a case.

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Study on Ontological Knowledge Integration of Micromachining for Collaborative Process

Liang

2023

J. Adv. Manuf. Syst.

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In collaborative manufacturing environment, the knowledge integration in collaborative process is very crucial, especially the heterogeneous information distributed among various cooperative suppliers. To tackle the optimization of knowledge consolidation in co-manufacturing, a knowledge integration with ontological framework is proposed in this study. First, by representing the collaborative business activities for cooperative suppliers, an architecture of knowledge integration with ontological schema is generated. The ontological model of knowledge concepts is explored in terms of the analysis of the ontological structure of knowledge. Aiming at the concept, an approach of ontology integration on the basis of ontological similarity is promoted. There are two portions included in this approach, mapping and combination, which are implemented through the analysis of similarity in two ontologies namely universal and regional. To integrate the two ontologies, the relations and restrictions among fields are definitely depicted by the Semantic Web Rule Language. Eventually, the presented framework is illustrated through a case study, and the outcomes satisfy the needs of knowledge combination to assure that the effectiveness of the presented method is confirmed.

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View updates and constraint validations in collaborative design environments

Cited by 4 publications

References 11 publications

Collaborative design by sharing multiple-level encryption files

Collaborative design by sharing multiple-level encryption files

Ontology-based information integration and sharing for collaborative part and tooling development

Study on Ontological Knowledge Integration of Micromachining for Collaborative Process

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