Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

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Multi-target regression and cross-validation for non-isothermal glass molding experiments with small sample sizes

2023 , Mende, Hendrik , Kiroriwal, Saksham , Pfrommer, Julius , Schmitt, Robert H. , Beyerer, Jürgen

Machine learning has become a core part of smart factories and Industry 4.0. In our work, we extend the use of machine learning for quality prediction of a thin glass product formed using a Non-isothermal Glass Moulding (NGM) process. As the form shape of a glass lens requires multiple variables to describe, Multi-Target Regression (MTR) is suitable for the same. Many MTR models are able to provide intuitive insights into the prediction target(s). We present a data pipeline that employs bootstrapping-inspired sampling for robust feature selection, modelling and validation for small dataset. The results demonstrate how MTR models can be used for prediction with dataset with high dimensional time series input and multiple targets.

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Cyber-physical systems in manufacturing

2016 , Monostori, László , Kádár, Botond , Bauernhansl, Thomas , Kondoh, Shinsuke , Kumara, Soundar R. , Reinhart, Gunther , Sauer, Olaf , Schuh, Günther , Sihn, Wilfried , Ueda, Kanji

One of the most significant advances in the development of computer science, information and communication technologies is represented by the cyber-physical systems (CPS). They are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the Internet. Cyber-physical production systems (CPPS), relying on the latest, and the foreseeable further developments of computer science, information and communication technologies on one hand, and of manufacturing science and technology, on the other, may lead to the 4th industrial revolution, frequently noted as Industrie 4.0. The paper underlines that there are significant roots in general - and in particular to the CIRP community - which point towards CPPS. Expectations towards research in and implementation of CPS and CPPS are outlined and some case studies are introduced. Related new R&D challenges are highlighted.

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Der Spitzencluster it's OWL auf dem Weg zu Industrie 4.0

2014 , Gausemeier, Jürgen , Dumitrescu, Roman , Jasperneite, Jürgen , Kühn, Arno , Trsek, Henning

Im Rahmen des BMBF-Spitzenclusters vollziehen der Maschinenbau, die Elektro- und die Automobilzulieferindustrie der Region Ostwestfalen-Lippe den Wandel von der Mechatronik zu vernetzten Systemen mit einer inhärenten Intelligenz. In insgesamt 46 Projekten entsteht eine Technologieplattform mit Fokus auf die Bereiche Selbstoptimierung, Mensch-Maschine-Interaktion, Intelligente Vernetzung, Energieeffizienz und Systems Engineering. Der Beitrag beschreibt konkrete Anwendungen auf der Basis dieser Technologieplattform, die dem Leitbild Industrie 4.0 folgen.

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