Disruptive technologies have the potential to change markets dramatically. The switch from internal combustion engines to electrical engines is such a change. But electric engines for vehicles are only the catalyst for the real change. Most significantly, the architecture and role of information and communication technology (ICT) will change for the vehicle of the future. This paper discusses the results of a study conducted in Germany on the role of ICT architectures. Furthermore, it will present an experimental platform that implements the vision of this study.

Abstract-Life cycles of many products are becoming shorter. In addition, the number of variants of one product is growing. As a fact, volume of one specific product that is being manufactured is decreasing. This leads to more frequent modifications of production lines. To cope with these changes, adaptable manufacturing systems are required. Current manufacturing systems can only be adapted to certain (predefined) situations. Other changes require high effort accompanied with high cost and setup time. In this paper, we focus on adaptivity with respect to IT systems. To increase the adaptability of IT systems for automation, we propose a model-based plug & play approach for integrating new stations. This helps in reducing changeover time and efforts. We propose different models describing stations and their capabilities, the setup of the factory, and the production plans. The system is then monitored automatically and the production is planned using models @ run-time. To abstract from different platforms and communication technologies data transfer is handled by a middleware. We evaluate our approach using an industrial production system used for educational purposes.

Manufacturing enterprises can only stay profitable if they manage to flexibly respond to changes in markets by adapting their products, product variants, and product volumes. To support such variety in products, we suggest a capabilitybased approach for production planning and scheduling. Production plans and machines are described in terms of required capabilities and provided capabilities respectively. Additionally, the topology of the factory is described. We propose to combine these descriptions to automatically generate production schedules that consider the material flow in the factory. For each production plan, our approach generates a valid schedule for the currently available machines in the factory without manually reconfiguring the software. The evaluation of the approach on an industrial production system used for educational purposes shows the suitability of this approach.

In times of fast changing markets and short product life-cycles manufacturing systems have to be adaptable and able to support a variety in products and product volumes. Production has to be product-driven and switching between different products should be possible with little manual intervention. We suggest an action sequence generation approach that tailors the control programs of resources to product needs. The approach requires a model of the available resources with their capabilities and internal material flow, the material flow between resources as well as a product description. An action sequence can then be generated out of these models and later translated into an executable action sequence. The action sequence can be automatically downloaded and executed on a resource. The approach is evaluated on an educational production system with industrial components.

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