Bøger i Technologien Fur Die Intelligente Automation serien

In diesem Open-Access-Tagungsband sind die besten Beiträge des 8. Jahreskolloquiums "Bildverarbeitung in der Automation" (BVAu 2022) enthalten. Das Kolloquium fand am 02. November 2022 auf dem Innovation Campus Lemgo statt.Die vorgestellten neuesten Forschungsergebnisse auf den Gebieten der industriellen Bildverarbeitung erweitern den aktuellen Stand der Forschung und Technik. Die in den Beiträgen enthaltenen anschaulichen Anwendungsbeispiele aus dem Bereich der Automation setzen die Ergebnisse in den direkten Anwendungsbezug.

In diesem Open-Access-Tagungsband sind die besten Beiträge des 9. Jahreskolloquiums "Kommunikation in der Automation" (KommA 2018) und des 6. Jahreskolloquiums "Bildverarbeitung in der Automation" (BVAu 2018) enthalten. Die Kolloquien fanden am 20. und 21. November 2018 in der SmartFactoryOWL, einer gemeinsamen Einrichtung des Fraunhofer IOSB-INA und der Technischen Hochschule Ostwestfalen-Lippe statt.Die vorgestellten neuesten Forschungsergebnisse auf den Gebieten der industriellen Kommunikationstechnik und Bildverarbeitung erweitern den aktuellen Stand der Forschung und Technik. Die in den Beiträgen enthaltenen anschaulichen Beispiele aus dem Bereich der Automation setzen die Ergebnisse in den direkten Anwendungsbezug.

This thesis describes the research done regarding communication reliability when using the Internet to realize the communications for cyber-physical systems (CPSs).

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models.

This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models.

This open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality prediction.

This dissertation proposes andinvestigates an isochronous wireless network for industrial controlapplications with guaranteed latencies and jitter. It consists of aTDMA-based medium access control, a dynamic resource allocation and theprovision of a global time base for the wired and the wireless network.

The objective of this dissertation is to design a concept that would allow to increase the flexibility of currently available Time Triggered Ethernet based (TTEB) systems, however, without affecting their performance and robustness.

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models.

This work proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation) and the BalTLCS (fuzzified balanced two-layer conflict solving) fusion algorithm to reduce the impact of conflicts on the fusion result.