An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

FESTivE: an information system method to improve product designers and environmental experts information exchanges

Effective collaboration between product designers and environmental experts is an important driver for the ecodesign practice in industry. This paper investigates the principal functions required for such an e ective collaboration and aims at facilitating them. Product designers should be able to integrate the environmental parameters into their activities, and to exchange information dynamically with the environmental expert whenever needed during the design process. Therefore, the IT system should be in itself dynamic and exible to the integration of new concepts (knowledge, software). Recent developments in Model Driven Engineering (MDE) are showing some interesting results to gain exibility and dynamism in the IT system. Combining software interoperability using model federation based on MDE with the speci city of ecodesign practice in industry this paper proposes the FESTivE method for Federate EcodeSign Tool modEls. Experimented in two different industrial contexts the practical feasibility of FESTivE has been validated with practitioners. Results on the e ects of using FESTivE in industry shows that product designers and environmental experts are more equipped to anticipate and to respond to each other's needs at each stage of the design process of product or service

A metamodel to annotate knowledge based engineering codes as enterprise knowledge resources

The encoding of Knowledge Based Engineering (KBE) software applications is becoming a prominent tool for the automation of knowledge intensive tasks carried out using Computer Aided Design (CAD) technology. However, limitations exist on the ability to manage the engineering knowledge models embedded in these executable KBE applications. This research proposes a metamodel to annotate encoded KBE applications. Resulting from the annotation, XKMs become explicit knowledge resources whose content can be better accessed and managed. The attachment of metadata to data sets in enterprise repositories is a necessary step to identify and index them so they can be queried, browsed and changed. The sophistication of metadata models for these data “items” ranges from the simple indexing using numbers to more sophisticated representations describing their context information (i.e. author, creation date, etc.), their internal structure and their content. Current engineering data repositories like Product Data Management and Product Lifecycle Management systems offer predefined metamodels to annotate a range of engineering data items including CAD files or special types of documents. At the moment, there is no metadata model specifically designed to annotate KBE codes. In this situation, an undifferentiated metadata model needs to be used for XKMs. However, in this case the only information retained by the system about them would be context metadata. Once an instance of the metadata is attached to an XKM, it can be used as its identifier within an enterprise data repository. The proposed metamodel contains abstract entities to annotate XKMs. The resulting descriptive model for an XKM pays attention to its internal structure and its operation at different levels of granularity. The particular design of the proposed metamodel positions it at a level of abstraction between non executable domain knowledge models and executable KBE applications. This design choice is made to support the use of the metadata not only as an informative model but also as an executable one. The achievement of this target is becoming possible through the emergence of semantic modelling standards that allow the description of data models independently from the language of implementation. Using this approach, the generation of code and metadata is made automatically using mapping rules resulting from the semantic agreement between models and specific syntax rules. The immediate application of the developed metamodel is to annotate XKMs within PLM systems. The approach shall contribute not only to systematically store instances of XKMs but also to manage the lifecycle of the engineering knowledge encoded within them. The proposed representation provides a more comprehensive approach for non KBE language experts to understand the code. On this basis, the change on the metamodels can be automatically traced back to the code and vice-versa. During the research, evidence has been gathered from the community of KBE technology users and vendors on the need to support this research effort. In the long term, the research contributes to the use of PLM systems as a platform for engineering knowledge management.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A manufacturing core concepts ontology to support knowledge sharing

Knowledge sharing across domains is key to bringing down the cost of production and the time to market of products. This thesis is directed to improve the knowledge sharing capability of the present systems that use information and communication technologies. Systems for different domains have structures that are made up of concepts and relations with different semantic interpretations. Therefore, knowledge sharing across such domains becomes an issue. Knowledge sharing across multiple domains can be facilitated through a system that can provide a shared understanding across multiple domains. This requires a rigorous common semantic base underlying the domains across which to share knowledge. [Continues.

Supporting fine-grained generative model-driven evolution

In the standard generative Model-driven Architecture (MDA), adapting the models of an existing system requires re-generation and restarting of that system. This is due to a strong separation between the modeling environment and the runtime environment. Certain current approaches remove this separation, allowing a system to be changed smoothly when the model changes. These approaches are, however, based on interpretation of modeling information rather than on generation, as in MDA. This paper describes an architecture that supports fine-grained evolution combined with generative model-driven development. Fine-grained changes are applied in a generative model-driven way to a system that has itself been developed in this way. To achieve this, model changes must be propagated correctly toward impacted elements. The impact of a model change flows along three dimensions: implementation, data (instances), and modeled dependencies. These three dimensions are explicitly represented in an integrated modeling-runtime environment to enable traceability. This implies a fundamental rethinking of MDA

Manufacturing systems interoperability in dynamic change environments

The benefits of rapid i.e. nearly real time, data and information enabled decision making at all levels of a manufacturing enterprise are clearly documented: the ability to plan accurately, react quickly and even pre-empt situations can save industries billions of dollars in waste. As the pace of industry increases with automation and technology, so the need for accurate, data, information and knowledge increases. As the required pace of information collection, processing and exchange change so to do the challenges of achieving and maintaining interoperability as the systems develop: this thesis focuses on the particular challenge of interoperability between systems defined in different time frames, which may have very different terminology. This thesis is directed to improve the ability to assess the requirement for systems to interoperate, and their suitability to do so, as new systems emerge to support this need for change. In this thesis a novel solution concept is proposed that assesses the requirement and suitability of systems for interoperability. The solution concept provides a mechanism for describing systems consistently and unambiguously, even if they are developed in different timeframes. Having resolved the issue of semantic consistency through time the analysis of the systems against logical rules for system interoperability is then possible. The solution concept uses a Core Concept ontology as the foundation for a multi-level heavyweight ontology. The multiple level ontology allows increasing specificity (to ensure accuracy), while the heavyweight (i.e. computer interpretable) nature provides the semantic and logical, rigour required. A detailed investigation has been conducted to test the solution concept using a suitably dynamic environment: Manufacturing Systems, and in particular the emerging field of Manufacturing Intelligence Systems. A definitive definition for the Manufacturing Intelligence domain, constraining interoperability logic, and a multi-level domain ontology have been defined and used to successfully prove the Solution Concept. Using systems from different timeframes, the Solution concept testing successfully identified systems which needed to interoperate, whether they were suitable for interoperation and provided feedback on the reasons for unsuitability which were validated as correct against real world observations