Feature-based ontological framework for semantic interoperability in product development
RK Gupta, B Gurumoorthy - Advanced Engineering Informatics, 2021 - Elsevier
Advanced Engineering Informatics, 2021•Elsevier
An essential requirement in integrating tasks in product development is to have a seamless
exchange of product information through the entire product lifecycle. A key challenge in the
integration is the exchange of shape semantics in terms of understandable labels and
representations. A unified taxonomy is proposed to represent, classify, and extract shape
features. This taxonomy is built using the Domain-Independent Form Feature (DIFF) model
as the representation of features. All the shape features in a product model are classified …
exchange of product information through the entire product lifecycle. A key challenge in the
integration is the exchange of shape semantics in terms of understandable labels and
representations. A unified taxonomy is proposed to represent, classify, and extract shape
features. This taxonomy is built using the Domain-Independent Form Feature (DIFF) model
as the representation of features. All the shape features in a product model are classified …
Abstract
An essential requirement in integrating tasks in product development is to have a seamless exchange of product information through the entire product lifecycle. A key challenge in the integration is the exchange of shape semantics in terms of understandable labels and representations. A unified taxonomy is proposed to represent, classify, and extract shape features. This taxonomy is built using the Domain-Independent Form Feature (DIFF) model as the representation of features. All the shape features in a product model are classified under three main classes, namely, volumetric features, deformation features and free-form surface features. Shape feature ontology is developed using the unified taxonomy, which brings the shape features under a single reasoning framework. One-to-many reasoning framework is presented for mapping semantically equivalent information (label and representation) of the feature to be exchanged to target applications, and the reconstruction of the shape model automatically in that target application. An algorithm has been developed to extract the semantics of shape features and construct the model in the target application. The algorithm developed has been tested for shape models taken from literature and test cases are selected based on variations of topology and geometry. Results of exchanging product information are presented and discussed. Finally, the limitations of the proposed method for exchanging product information are explained.
Elsevier