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Today's models in production engineering are mainly based on quasi-stationary design assumptions. With increasing dynamics, models reflecting the nonlinear characteristics of production are becoming increasingly relevant. Several approaches have been formulated to design self-organizing systems, leading to good results with regards to the efficiency in which dynamics are mastered by local interaction of a system's entities. While in self-organization a system's characteristics emerge bottom-up, effectiveness is designed into a system by an analytical, top-down design approach. The paper discusses how a target oriented analytical design approach can be combined with the concept of self-organization and shows its application and impact on practical examples.

Augmented Reality (AR) has recently found high attention in mobile shopping apps such as in domains like furniture or decoration.Here, the developers of the apps focus on the positioning of atomic 3D objects in the physical environment. With this focus, they neglect the configuration of multi-faceted 3D object composition according to the user needs and environmental constraints. To tackle these challenges, we present a model-based approach to support AR-assisted product configuration based on the concept of Dynamic Software Product Lines. Our approach splits products (e.g. table) into parts (eg. tabletop, table legs, funnier) with their 3D objects and additional information (e.g. name, price). The possible products, which can be configured out of these parts, are stored in a feature model. At runtime, this feature model can be used to configure 3D object compositions out of the product parts and adapt to user needs and environmental constraints. The benefits of this approach are demonstrated by a case study of configuring modular kitchens with the help of a prototypical mobile-based implementation.

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