Production-Related Service Systems Based on Big-Data-Analysis
Today, modern production technology delivers a multitude of process and product data for the efficient control of machines or production processes. So far, these data are only stored locally in so-called data islands and further processed. Through the intelligent linking and correlation of these data islands previously unknown relationships can be identified and used for process optimization. However, for small and medium-sized enterprises (SMEs) in particular, this poses a challenge because, on the one hand, the methods and, on the other hand, the potentials are not sufficiently well known.
The aim of the collaborative research project ProData is to enable companies - especially SMEs - to recognize the potential of modern data analysis and to use it economically, without first having to make significant start-up investments (e.g. sensor technology, competencies, network networking).
Services including the necessary business models are to be developed and demonstrated on the basis of concrete application cases. The services are based on needs of the customers, in that case companies to be identified in the production environment. Furthermore the data required to fulfill the service is defined. The following categories are considered: (i) data is present but not exploited, (ii) data accumulates but is only stored volatile (e.g., SPS), and (iii) a data basis is absent; additional sensors and measuring technology is required. In addition, more transferable and easier-to-use big data analysis methods will be developed, which will contribute to increasing value in production. Finally, the business model, including the framework conditions and a sales concept, in which the services provide the highest possible overall economic benefit, are developed.
Companies should thus be enabled to identify optimization potential and needs in their own production-related processes regarding data-driven services. The services are consolidated and made available in the form of business models. This procedure ensures that there is a transferability and replicability of the results. The use of standardized sensors and non-proprietary software solutions ensures that the services and the associated Big-Data-Analysis are subsequently available to the SME users in the manufacturing industry and can be used economically.
Federal Ministry of Education and Research (Germany)
Karlsruher Institute of Technology (KIT) – wbk Institute of Production Science (Prof. Dr.-Ing. Gisela Lanza)
Karlsruher Institute of Technologie (KIT) – AIFB Institute of Applied Informatics and Formal Description Methods (Prof. Dr. York Sure-Vetter)
Robert Bosch GmbH, Carl Zeiss Industrielle Messtechnik GmbH, Balluff GmbH, Arend Prozessautomation GmbH, CeramTec GmbH, Gebr. Pfeiffer SE, Hilscher Gesellschaft für Systemautomation mbH, Seuffer GmbH & Co. KG, USU Software AG