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

被引:77
作者
Chung, PWH [1 ]
Cheung, L
Stader, J
Jarvis, P
Moore, J
Macintosh, A
机构
[1] Univ Loughborough, Dept Comp Sci, Loughborough LE11 3TU, Leics, England
[2] Univ Edinburgh, AI Applicat Inst, Edinburgh, Midlothian, Scotland
基金
英国工程与自然科学研究理事会;
关键词
workflow management; adaptive workflow; knowledge-based process management; process modelling; agent selection;
D O I
10.1016/S0950-7051(02)00080-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 [8,18] and using knowledge-based techniques to provide more flexible process management support than is possible using current workflow systems [4,19]. 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. (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:149 / 160
页数:12
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