Modelling Production System Families with AutomationML
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Institute of Electrical and Electronics Engineers Inc. (IEEE)Date
2020-09-01Citation
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/ETFA46521.2020.9211894Editor's Version
https://doi.org/10.1109/ETFA46521.2020.9211894Subjects
AutomationML; Feature Modelling; Model-Driven Engineering; Product Lines; Variability; InformáticaNote
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Rights
© Institute of Electrical and Electronics EngineersAbstract
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
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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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