Petri net-based process monitoring: a workflow management system for process modelling and monitoring

Nowadays business process management is becoming a fundamental piece of many industrial processes. To manage the evolution and interactions between the business actions it is important to accurately model the steps to follow and the resources needed by a process. Workflows provide a way of describin...

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Detalles Bibliográficos
Autores: Pla Planas, Albert, Gay Sacristán, Pablo, Meléndez i Frigola, Joaquim, López Ibáñez, Beatriz
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2014
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/9597
Acceso en línea:http://hdl.handle.net/10256/9597
Access Level:acceso abierto
Palabra clave:Petri, Xarxes de
Petri nets
Cicle de treball
Workflow
Descripción
Sumario:Nowadays business process management is becoming a fundamental piece of many industrial processes. To manage the evolution and interactions between the business actions it is important to accurately model the steps to follow and the resources needed by a process. Workflows provide a way of describing the order of execution and the dependencies between the constituting activities of business processes. Workflow monitoring can help to improve and avoid delays in industrial environments where concurrent processes are carried out. In this article a new Petri net extension for modelling workflow activities together with their required resources is presented: resource-aware Petri nets (RAPN). An intelligent workflow management system for process monitoring and delay prediction is also introduced. Resource aware-Petri nets include time and resources within the classical Petri net workflow representation, facilitating the task of modelling and monitoring workflows. The workflow management system monitors the execution of workflows and detects possible delays using RAPN. In order to test this new approach, different services from a medical maintenance environment have been modelled and simulate