Modelling Production System Families with AutomationML
Entidad
UAM. Departamento de Ingeniería InformáticaEditor
Institute of Electrical and Electronics Engineers Inc. (IEEE)Fecha de edición
2020-09-01Cita
10.1109/ETFA46521.2020.9211894
A. Garmendia, M. Wimmer, A. Mazak-Huemer, E. Guerra and J. de Lara, Modelling Production System Families with AutomationML, 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vienna, Austria, 2020, pp. 1057-1060
ISSN
1946-0740ISBN
978-1-7281-8956-7DOI
10.1109/ETFA46521.2020.9211894Versión del editor
https://doi.org/10.1109/ETFA46521.2020.9211894Materias
AutomationML; Feature Modelling; Model-Driven Engineering; Product Lines; Variability; InformáticaNota
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© Institute of Electrical and Electronics EngineersResumen
The description of families of production systems usually relies on the use of variability modelling. This aspect of modelling is gaining increasing interest with the emergence of Industry 4.0 to facilitate the product development as new requirements appear. As a consequence, there are several emerging modelling techniques able to apply variability in different domains. In this paper, we introduce an approach to establish product system families in AutomationML. Our approach is based on the definition of feature models describing the variability space, and on the assignment of presence conditions to AutomationML model elements. These conditions (de-)select the model elements depending on the chosen configuration. This way, it is possible to model a large set of model variants in a compact way using one single model. To realize our approach, we started from an existing EMF-based AutomationML workbench providing graphical modelling support. From these artifacts, we synthesized an extended graphical modelling editor with variability support, integrated with FeatureIDE. Furthermore, we validated our approach by creating and managing a production system family encompassing six scenarios of the Pick and Place Unit Industry 4.0 demonstrator
Lista de ficheros
Google Scholar:Garmendia, Antonio
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Wimmer, Manuel
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Mazak-Huemer, Alexandra
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Guerra, Esther
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De Lara, Juan
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