Methods and tools for supporting industrial design innovation

The introduction of information technology (IT) systems to support designers’ activities and data management have profoundly affected company structure and design organization. This evolution has brought the introduction of systematic methods, close to information tools skills and prerogatives, using computer management and data recovery skills as main design support. The use of the IT also improved information exchange among different work figures involved during product development process. In this direction authors have intended to analyze the role and the implementation of systematic methods and tools within industrial designer area of the design process and their impact on the conceptual design phase in particular. Consequently, the research has been developed primarily in reference to design methods able to support the strict ideation stage of the Conceptual Design, that can be referred to two typologies: knowledge based and functional approaches. Subsequently authors have analyzed the information tools currently used during design process, as CAD systems, and some innovative, as Virtual and Augmented Reality tools, that can be used within industrial design area. The result of the study has been a formalization of the course followed during idea conceptual phase in order to include and to arrange the design methods and tools analysed. The research proposes a structured view of a process of product conceptualization, usually considered as mainly heuristic, focusing on the integration of methods and tools to support project and its communication. In this area the research has highlighted industrial designer role characteristics during design process, changeable in reference of project development level, and also some important new questions have been identified about the interaction between industrial designers and the other design areas involved in the process. In this direction the study has highlighted the need to support knowledge exchange and recovery, introducing the possibility to extend the research to the whole process and integrate industrial design and engineering collaboration in a more effective way. Keywords: Conceptual design process, Systematic innovation, Knowledge management, Integration</p

A formal verification framework and associated tools for enterprise modeling : application to UEML

The aim of this paper is to propose and apply a verification and validation approach to Enterprise Modeling that enables the user to improve the relevance and correctness, the suitability and coherence of a model by using properties specification and formal proof of properties

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

OntoEng: A design method for ontology engineering in information systems

This paper addresses the design problem relating to ontology engineering in the discipline of information systems. Ontology engineering is a realm that covers issues related to ontology development and use throughout its life span. Nowadays, ontology as a new innovation promises to improve the design, semantic integration, and utilization of information systems. Ontologies are the backbone of knowledge-based systems. In addition, they establish sharable and reusable common understanding of specific domains amongst people, information systems, and software agents. Notwithstanding, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. On the basis of the gathered experience during the development of V4 Telecoms Business Model Ontology as well as the conducted integration of the related literature from the design science paradigm, this paper introduces OntoEng and its application as a novel systematic design method for ontology engineering

Requirements for Information Extraction for Knowledge Management

Knowledge Management (KM) systems inherently suffer from the knowledge acquisition bottleneck - the difficulty of modeling and formalizing knowledge relevant for specific domains. A potential solution to this problem is Information Extraction (IE) technology. However, IE was originally developed for database population and there is a mismatch between what is required to successfully perform KM and what current IE technology provides. In this paper we begin to address this issue by outlining requirements for IE based KM

Guidelines for a Dynamic Ontology - Integrating Tools of Evolution and Versioning in Ontology

Ontologies are built on systems that conceptually evolve over time. In addition, techniques and languages for building ontologies evolve too. This has led to numerous studies in the field of ontology versioning and ontology evolution. This paper presents a new way to manage the lifecycle of an ontology incorporating both versioning tools and evolution process. This solution, called VersionGraph, is integrated in the source ontology since its creation in order to make it possible to evolve and to be versioned. Change management is strongly related to the model in which the ontology is represented. Therefore, we focus on the OWL language in order to take into account the impact of the changes on the logical consistency of the ontology like specified in OWL DL