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A deductive system for proving workflow models from operational procedures

Rasmussen, Rune K. & Brown, Ross A. (2012) A deductive system for proving workflow models from operational procedures. Future Generation Computer Systems, 28(5), pp. 732-742.

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Abstract

Many modern business environments employ software to automate the delivery of workflows; whereas, workflow design and generation remains a laborious technical task for domain specialists. Several differ- ent approaches have been proposed for deriving workflow models. Some approaches rely on process data mining approaches, whereas others have proposed derivations of workflow models from operational struc- tures, domain specific knowledge or workflow model compositions from knowledge-bases. Many approaches draw on principles from automatic planning, but conceptual in context and lack mathematical justification. In this paper we present a mathematical framework for deducing tasks in workflow models from plans in mechanistic or strongly controlled work environments, with a focus around automatic plan generations. In addition, we prove an associative composition operator that permits crisp hierarchical task compositions for workflow models through a set of mathematical deduction rules. The result is a logical framework that can be used to prove tasks in workflow hierarchies from operational information about work processes and machine configurations in controlled or mechanistic work environments.

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ID Code: 48181
Item Type: Journal Article
Keywords: Workflow, Planning, Petri-net, Automation, Management, Modelling
DOI: 10.1016/j.future.2012.01.001
ISSN: 0167-739X
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Simulation and Modelling (080110)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Virtual Reality and Related Simulation (080111)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Systems not elsewhere classified (080699)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Information Systems
Copyright Owner: Copyright 2012 Elsevier B.V.
Deposited On: 23 Jan 2012 11:21
Last Modified: 15 Sep 2013 05:08

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