Knowledge driven system architecture to support collaborative product development in the extended enterprise
Abstract
In recent times, the global engineering environment has led to the distribution of product life cycle information and knowledge affecting the collaboration throughout product development. Although information technologies, such as the Internet, provide a partial solution to support such collaboration, there is still a need to support decision making by providing the right information and knowledge in the place, time and format required by the geographically distributed companies. The sources of this knowledge are the experience of individuals, published literature, as well as the manufacturing process and resource capabilities. Hence, it ensures the production of a better and more cost effective product in less time. The research presented in this thesis proposes a knowledge driven system architecture to support collaborative product development (KdCPD). Furthermore, a novel approach for identifying, capturing and representing knowledge of a geographically distributed extended enterprise was developed as part of the research. This knowledge representation, which is referred to as Manufacturing Knowledge Model, is the basis of the proposed system architecture. In this research, a reference framework was adopted for the development of the KdCPD system architecture. This framework guided the identification of information and knowledge driven manufacturing activities as well as the modelling of the Manufacturing Knowledge Model. Based on this, a Knowledge driven Collaborative Product Development (KdCPD) system architecture was designed and a system prototype was implemented using object oriented enabling technologies. Finally, several experiments were conducted in the system prototype using several case studies in order to simulate the development of injection moulded parts among geographically distributed companies after the conceptual design has been agreed. The results of these experiments demonstrated how the KdCPD system supports decision making by providing the right information and knowledge in the place, time and format required. This confirmed the contribution of this research to the next generation of collaborative systems.Publisher
University of WolverhamptonType
Thesis or dissertationLanguage
enDescription
A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyCollections
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