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Knowledge-based process management – an approach to handling adaptive workflow

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journal contribution
posted on 30.08.2006 by Paul Chung, Larry Y.C. Cheung, J. Stader, P. Jarvis, J. Moore, A. Macintosh
In recent years, many organisations have found enterprise modelling, especially business process modelling, to be an effective tool for managing organisational change. The application of business processing modelling has brought benefits to many organisations, but the models developed tend to be used for reference during business operations and re-engineering activities; they rarely play an active role in supporting the day-to-day execution of the processes. While workflow management systems are widely used for the streamlined management of "administrative" business processes, current systems are unable to cope with the more dynamic situations encountered in ad-hoc and collaborative processes [1]. A system that supports complex and dynamically changing processes is required. There is increasing interest in making workflow systems more adaptive [8][20] and using knowledge-based techniques to provide more flexible process management support than is possible Published in Knowledge-based Systems, Vol 16, 2003, pp149-160 Page 2 using current workflow systems [4][21]. This paper describes the results of a collaborative project between Loughborough University and the University of Edinburgh. ICI and Unilever were industrial partners on the project, providing real business requirements in the application domain. The project investigated the use of ontologies, agents and knowledge based planning techniques to provide support for adaptive workflow or flexible workflow management, especially in the area of new product development within the chemical industries.

History

School

  • Science

Department

  • Computer Science

Pages

169318 bytes

Citation

CHUNG et al, 2003. Knowledge-based process management – an approach to handling adaptive workflow. Knowledge-based systems, 16 (3), pp. 149-160

Publisher

© Elsevier

Publication date

2003

Notes

This journal was published in the journal, Knowledge-based systems [© Elsevier] and is also available at: http://www.sciencedirect.com/science/journal/09507051

ISSN

0950-7051

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