A METHODOLOGY FOR KEE SYSTEMS TARGET CASCADING

The main aim of this paper is to present a methodology developed within the European Project VIVACE to guide the design and implementation of a Knowledge Enabled Engineering (KEE) system in a Virtual Enterprise. The proposed methodology tries to overcome some of the limitations which characterise traditional methods for Target Cascading, promoting a more collaborative and iterative approach to derive system specifications (in terms of advanced knowledge functionalities) from initial high-level targets. Social and behavioural aspects of Knowledge Management play a crucial role when many different users, knowledge experts, and process owners are involved in the Knowledge Management System (KMS) development. A well designed methodology is needed, therefore, to enhance communication and information sharing among design teams, to promote requirements merging and to take care both of the technological and behavioural aspects of the implementation. Initial business targets have been step-by-step decomposed into a set of sub-problems (Service Requirements, Knowledge Issues, and Knowledge Challenges) in the form of simple sentences in natural language. Then Quality Function Deployment (QFD) matrixes have been used to identify the set of functionalities to be implemented in the system, addressing the most important knowledge-related problems outlined in the cascading activity.

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