Use Cases
In six pilot projects, companies and research institutions in the AI marketplace developed AI solutions for specific use cases.
The goal of Ubermetrics' project is to an AI application that relevant information from unstructured or semi-structured texts (e.g. online reviews, complaint emails, service reports, complaint reports), analyzes them analyzed and systematically made available to a developer. available to a developer. The application can be used, for example, in the context of the targeted optimization of system components.
How can service technicians be optimally be supported? This question is being addressed by a pilot project of Diebold Nixdorf Systems together with Fraunhofer IOSB-INA. The goal is to develop an AI application that reads out and analyzes service and sensor data from ATMs from the field and analyzes them. Based on this differentiated repair instructions for service technicians. generated for service technicians. The data basis is an existing service platform.
Artificial intelligence has the potential to change the way how fundamentally change the way we work and do business. CLAAS GmbH & Co. KGaA, an international manufacturer of international agricultural machinery manufacturer, has recognized this potential and is testing the AI marketplace together with the Fraunhofer Institutes IEM and IPK a special use case for the integration of AI in Computer Aided Design (CAx).
Currently, vehicle diagnostics in a workshop comprehensive knowledge and is associated with an extensive amount of work. workload. Hella Gutmann's goal is therefore therefore, to develop an AI application for AI-supported diagnosis and identification potentially defective vehicle components on the basis of historical vehicle data vehicle data (e.g. fault codes, sensor readings and KM statuses) and to develop a further variety of data sources sources (e.g. invoice data, repair information, etc.). integrate.
The focus of the Westaflex project with the Fraunhofer IEM is is an AI application that can be used to plan the sequence of of of production orders is optimized. For this purpose real-time data from the production control system and from machines machines will be evaluated in order to extract information on the optimal extract.
In this project a setup process in an automated manufacturing process is to be optimized with the help of AI. and replace the manual "teach-in" process that has been used up to now. In addition, the anticipated manufacturability of of new specifications can be assessed automatically. be able to be automated. This pilot project is being carried out by düspohl Maschinenbau GmbH and the the Fraunhofer IEM.
