Affiliation:
1. TU Dortmund University Department of Biochemical and Chemical engineering, Laboratory of Equipment Design Emil-Figge-Straße 68 44227 Dortmund Germany
2. TU Dresden University Process-to-Order Lab Helmholtzstraße 16 01069 Dresden Germany
3. Merck Electronics KGaA EL-OTE Frankfurter Straße 250 64293 Darmstadt Germany
Abstract
AbstractImage analysis presents a set of powerful methods to receive additional information about multiphase processes. It enables the development of advanced applications for process monitoring and optimization or, so‐called, soft sensors. However, the integration of advanced smart sensor systems based on image analysis into the process control system presents a complex task. To address this challenge, a modular automation concept offers a standardized interface to integrate modules. This paper presents an integration profile as a service specification that allows a plug‐and‐measure integration of smart visual sensors into modular plants. To verify the concept, we applied it to three different use cases. At the end, we discuss open challenges in the integration of complex analysis systems with multidimensional data streams into modular plants.
Funder
Bundesministerium für Wirtschaft und Klimaschutz
Subject
Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry
Reference30 articles.
1. Modulbasierte Produktion in der Prozessindustrie ‐ Auswirkungen auf die Automation im Umfeld von Industrie 4.0: Empfehlungen des AK Modulare Automation zur NE148 der Namur ZVEI – Zentralverband Elektrotechnik und Elektronikindustrie e. V. Frankfurt/Main2015.
2. Deep Learning for Computer Vision: A Brief Review
3. The Machine Learning Life Cycle in Chemical Operations – Status and Open Challenges
4. V.Khaydarov S.Heinze M.Graube A.Knupfer M.Knespel S. Merkelbach L.Urbas in2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) IEEE Piscataway NJ2020.