Industrielle Signalverarbeitung, Mustererkennung

DnSPro: Sensor- und Informationsfusion für dezentral kooperierende sensorbasierende Subsysteme für Industrie-4.0-Produktionsanlagen

01.11.2015 bis 31.01.2019

With the project of the future Industry 4.0 we now have the chance to raise the flexibility and the energy and resource efficiency of production processes to a new level by implementing intelligent control and networking. Electronics and sensor technology are crucial because they belong to the outstanding strengths of Germany’s small and medium enterprises (SMEs). Industry 4.0 applications require diverse sensor systems. In order to improve further the company processes, the sensor data are to be immediately and directly made accessible.

The project aims at creating a basis for intelligent Industry 4.0 production plants which are able to adapt quickly and flexibly to changing conditions with a significantly higher grade of availability. By the example of a filling process for any liquids we want to show the complex interaction between individual functional modules and the overall system. The plants should adjust autonomously to the product to be manufactured considering its characteristics and plant’s parameters. For this purpose, we integrate manifold sensory functions as well as intelligent autonomous self-diagnostics capabilities of the individual components and processes. We pay particular attention to guaranteeing continuous dynamic data security.

Due to decentralised control autonomously acting plant parts allow economical production, since they can be rapidly recombined when faced with changing production processes. By applying “smart” field devices plant parts are more and more conscious about their actual condition and even possible problems which may occur in future. Based on this principle, production of any sensor-actuator system becomes possible, as f. ex. the linking of flow, pressure, temperature and filling level sensors with valves and pumps.

This project is promoted by:
Bundesministerium für Bildung und Forschung (BMBF)
Funding Code: 16ES0391
Funding Lines: Sensorbasierte Elektroniksysteme für Industrie 4.0 (SElekt 4.0)
Employees: Alexander Dicks, M. Sc., Martyna Bator, B. Sc.
Martyna Bator, B. Sc.¹, Christian Wissel, M. Sc., Alexander Dicks, M. Sc., Prof. Dr.-Ing. Volker Lohweg²
Feature Extraction for a Conditioning Monitoring System in a Bottling Process.
In: 23rd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Sep 2018
¹ First Authors
² Last authors
Alexander Dicks, M. Sc.¹, Martyna Bator, B. Sc., Christian Wissel, M. Sc., Prof. Dr.-Ing. Volker Lohweg²
Bildverarbeitung im industriellen Umfeld von Abfüllanlagen
In: Kommunikation und Bildverarbeitung in der Automation, May 2019
¹ First Authors
² Last authors
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