Artificial intelligence in tomorrow's production The "Datenfabrik NRW" is a project of the leading-edge cluster it's OWL, in which the companies CLAAS and Schmitz Cargobull together with NTT Data, Duvenbeck Kraftverkehr and MotionMiners as well as the Fraunhofer Institutes IEM, IML, IOSB-INA and IAIS are developing a model for a data-driven factory of the future. Based on the most innovative processes and using artificial intelligence, the factory planning, production, logistics and enterprise architecture of the user companies will be analyzed and transformed in pilot areas. In addition, a strategic framework for change management and an IT infrastructure will be developed, so that technology and knowledge transfer will be widely accepted beyond the borders of North Rhine-Westphalia. The four participating Fraunhofer institutes will contribute their application-oriented research and practical implementation experience to the project and will take over the AI part in the project. The project focuses on three points: They identify and develop concrete solutions for the use of artificial intelligence in industrial production. They also facilitate the transfer of methods and technologies from science to companies in order to integrate AI-supported solutions into existing processes and company architectures. They also develop holistic change management that supports companies in organizing new processes for the use of artificial intelligence. The results will then be implemented directly in the factories of Claas and Schmitz Cargobull and should also be usable by other companies. Both KI.NRW and the leading-edge cluster it's OWL support the dissemination of the project results. The Datenfabrik.NRW project (duration 4 years) has a total volume of 14.5 million euros and is funded with 9.2 million euros by the state of North Rhine-Westphalia.

With a quarter of the gross value added, the manufacturing industry represents a significant economic factor in North Rhine-Westphalia (NRW). The increasing digitalization of production facilities and the resulting rise in data volumes offer the potential to boost performance through intelligent production environments and thus secure the competitiveness of NRW as a business location. To tap this potential, far-reaching changes are required within existing corporate structures and value creation networks. In shaping the successful transformation to a data-driven future factory with self-optimizing value creation processes, three fields of action emerge. First, intelligent solutions for industrial production must be developed. Second, a method and technology transfer is required that enables continuous integration of the solutions into existing processes and enterprise architectures. Thirdly, holistic change management must support companies in their transformation. In order to fully address the fields of action described, a new form of application-oriented research is required.

The aim of the Datenfabrik.NRW project is to design the digital transformation of a real production environment, which serves as a model with lighthouse character for manufacturing companies in NRW and beyond. Against this background, the factory planning, production, logistics, and enterprise architecture of the user companies CLAAS and Schmitz Cargobull are analyzed and transformed in pilot areas. Within the project duration of four years, the transformation process will be carried out in sub-areas in cooperation with research institutions and supplier companies in order to integrate key technologies such as artificial intelligence (AI) and at the same time conduct application-oriented research. At the same time, a strategic framework for change management and IT infrastructure is being developed. The research project will be accompanied by appropriate public relations work to ensure that the associated technology and knowledge transfer has a broad appeal beyond the borders of NRW.

The work program for implementing the lighthouse factory is divided into four transformation areas: Data-driven Production Engineering (DF), Data-driven Manufacturing, Data-driven Logistics and Data-driven Enterprise Architecture (Fig. 3). The transformation areas form a structured classification of various use cases of intelligent solutions for a data-driven future factory. The work program for implementing the lighthouse factory is accompanied by extensive broad transfer and professional project coordination. The transfer strategy envisages a multi-stage process consisting of sensitization, as-is analysis, empowerment and lighthouse platform. At each level, specific questions from manufacturing companies are answered, thus creating a broad transfer of the knowledge gained. Furthermore, the Lighthouse platform creates a digital lighthouse. Industrial companies can disclose selected data on it to enable the identification of new potentials and the development of innovative solutions by startups. In this way, the lighthouse factories and the platform will create an enormous impact for along the entire value chain. The concept for broad transfer provides for appropriate formats at each stage. These range from information sessions and events in the lighthouse factories to web-based tools for analyzing the current situation and innovation competitions based on real industry data to promote potential collaborations between proven industrial companies and startups.