TY - CONF

T1 - Modelling Production System Families with AutomationML

AU - Garmendia, Antonio

AU - Wimmer, Manuel

AU - Mazak-Huemer, Alexandra

AU - Guerra, Esther

AU - de Lara, Juan

N1 - doi: 10.1109/ETFA46521.2020.9211894

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Model-driven engineering

KW - AutomationML

KW - Product Lines

KW - Feature Modeling

KW - Variability

U2 - 10.1109/ETFA46521.2020.9211894

DO - 10.1109/ETFA46521.2020.9211894

M3 - Paper

SP - 1057

EP - 1060

T2 - 25th IEEE International Conference on Emerging Technologies and Factory Automation (EFTA)

Y2 - 8 September 2020 through 11 September 2020

ER -