Browsing by Author "Bermell-Garcia, Pablo"
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Item Open Access Categorisation of visualisation methods to support the design of Human-Computer Interaction systems(Elsevier, 2016-02-02) Li, Katie; Tiwari, Ashutosh; Alcock, Jeffrey R.; Bermell-Garcia, PabloDuring the design of Human-Computer Interaction (HCI) systems, the creation of visual artefacts forms an important part of design. On one hand producing a visual artefact has a number of advantages: it helps designers to externalise their thought and acts as a common language between different stakeholders. On the other hand, if an inappropriate visualisation method is employed it could hinder the design process. To support the design of HCI systems, this paper reviews the categorisation of visualisation methods used in HCI. A keyword search is conducted to identify a) current HCI design methods, b) approaches of selecting these methods. The resulting design methods are filtered to create a list of just visualisation methods. These are then categorised using the approaches identified in (b). As a result 23 HCI visualisation methods are identified and categorised in 5 selection approaches (The Recipient, Primary Purpose, Visual Archetype, Interaction Type, and The Design Process).Item Open Access A metamodel to annotate knowledge based engineering codes as enterprise knowledge resources(Cranfield University, 2007-04) Bermell-Garcia, Pablo; Fan, Ip-ShingThe 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.Item Open Access A new knowledge sourcing framework for knowledge-based engineering: an aerospace industry case study(Elsevier, 2016-12-16) Quintana-Amate, Santiago; Bermell-Garcia, Pablo; Tiwari, Ashutosh; Turner, Christopher J.New trends in Knowledge-Based Engineering (KBE) highlight the need for decoupling the automation aspect from the knowledge management side of KBE. In this direction, some authors argue that KBE is capable of effectively capturing, retaining and reusing engineering knowledge. However, there are some limitations associated with some aspects of KBE that present a barrier to deliver the knowledge sourcing process requested by industry. To overcome some of these limitations this research proposes a new methodology for efficient knowledge capture and effective management of the complete knowledge life cycle. The methodology proposed in this research is validated through the development and implementation of a case study involving the optimisation of wing design concepts at an Aerospace manufacturer. The results obtained proved the extended KBE capability for fast and effective knowledge sourcing. This evidence was provided by the experts working in the development of the case study through the implementation of structured quantitative and qualitative analyses.Item Open Access A new knowledge sourcing framework to support knowledge-based engineering development(Cranfield University, 2015-08) Quintana-Amate, Santiago; Ashutosh, Tiwari; Bermell-Garcia, PabloNew trends in Knowledge-Based Engineering (KBE) highlight the need for decoupling the automation aspect from the knowledge management side of KBE. In this direction, some authors argue that KBE is capable of effectively capturing, retaining and reusing engineering knowledge. However, there are some limitations associated with some aspects of KBE that present a barrier to deliver the knowledge sourcing process requested by the industry. To overcome some of these limitations this research proposes a new methodology for efficient knowledge capture and effective management of the complete knowledge life cycle. Current knowledge capture procedures represent one of the main constraints limiting the wide use of KBE in the industry. This is due to the extraction of knowledge from experts in high cost knowledge capture sessions. To reduce the amount of time required from experts to extract relevant knowledge, this research uses Artificial Intelligence (AI) techniques capable of generating new knowledge from company assets. Moreover the research reported here proposes the integration of AI methods and experts increasing as a result the accuracy of the predictions and the reliability of using advanced reasoning tools. The proposed knowledge sourcing framework integrates two features: (i) use of advanced data mining tools and expert knowledge to create new knowledge from raw data, (ii) adoption of a well-established and reliable methodology to systematically capture, transfer and reuse engineering knowledge. The methodology proposed in this research is validated through the development and implementation of two case studies aiming at the optimisation of wing design concepts. The results obtained in both use cases proved the extended KBE capability for fast and effective knowledge sourcing. This evidence was provided by the experts working in the development of each of the case studies through the implementation of structured quantitative and qualitative analyses.