A concept for virtual reality tools for design reviews
Proceedings of the conference on Visualization '98
Proceedings of the third international conference on Collaborative virtual environments
Distributed design review in virtual environments
Proceedings of the third international conference on Collaborative virtual environments
An integrative framework for knowledge extraction in collaborative virtual environments
GROUP '01 Proceedings of the 2001 International ACM SIGGROUP Conference on Supporting Group Work
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Usage-Oriented Evolution of Ontology-Based Knowledge Management Systems
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Change management in concurrent engineering from a parameter perspective
Computers in Industry
Capturing and reusing knowledge in engineering change management: A case of automobile development
Information Systems Frontiers
Automated end-user behaviour assessment tool for remote product and system testing
Expert Systems with Applications: An International Journal
International Journal of Business Information Systems
Re-engineering the Engineering Change Management process for a drawing-less environment
Computers in Industry
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In this paper, we analyze Engineering Changes (EC), which are modifications in forms, fits, functions, materials, or dimensions in components constituting the design. We propose a new approach for processing these changes within a Virtual Collaborative Design Environment. This environment, named Active Distributed Virtual Change Environment (ADVICE) offers an Engineering Change Management solution by merging graphical and parametric data involved in the process into a virtual platform, which improves the comprehension of users and hence decreases the time required for review. ADVICE provides smart user support for predicting Engineering Changes to be triggered due to a specific change and for offering priorities to Engineering Change Requests. This is managed by employing Sequential Pattern Mining techniques to process captured Engineering Change history with Prioritization and Change Propagation mechanisms. For verifying these mechanisms, experiments involving synthetic data are conducted. The experiments present the capability of ADVICE to facilitate Engineering Change Management.