NACH OBEN

Hesam Rezaee Ahvanouee
Hesam Rezaee Ahvanouee, M.Sc.
Wissenschaftlicher Mitarbeiter
 

Raum: ID 2/545
Telefon: +49 (0)234 / 32-15798
E-Mail


Postanschrift:
Ruhr-Universität Bochum
Fakultät Elektrotechnik und Informationstechnik
Lehrstuhl Automatisierungstechnik
Postfach ID 14
Universitätsstr. 150
44780 Bochum


Besucheranschrift:
Ruhr-Universität Bochum
Gebäude ID | Etage 2 | Raum 545
Universitätsstr. 150
44801 Bochum


Google Scholar:
https://scholar.google.com/citations?user=Up_jWfEAAAAJ&hl=en

LinkedIn:
https://at.linkedin.com/in/hesam-rezaee-9a778985

ORCID:
https://orcid.org/0000-0002-4371-5394

My research focuses on Industry 4.0, the next phase of industrial revolution characterized by smart automation, real-time data exchange, and cyber-physical systems. I explore how intelligent manufacturing and interconnected systems can enhance efficiency, flexibility, and responsiveness in modern production environments.

IEC 61499:
I work with IEC 61499, a standard for distributed control systems that supports modular, event-driven function blocks. It enables reconfigurable and scalable automation architectures, which are essential for realizing adaptive and decentralized Industry 4.0 systems.

Asset Administration Shell (AAS):
My research involves the Asset Administration Shell (AAS), a core concept in Industry 4.0 that provides a digital representation of assets. AAS enables standardized data exchange and interoperability between components, laying the foundation for seamless integration in smart factories.

AutomationML (AML):
I utilize AutomationML (AML), a neutral data format for exchanging plant engineering information. AML supports cross-domain integration by enabling consistent data sharing across mechanical, electrical, and control domains, promoting collaborative engineering.

Digital Twin:
I investigate Digital Twin technologies that create virtual models of physical assets or processes. These models mirror real-world behavior, enabling simulation, monitoring, and optimization, which significantly enhance predictive maintenance and operational efficiency.

2025:

  • Automatische Erstellung von Anlagenbeschreibungen mit Hilfe von Large Language Models
    Sebastian Belzer, Bachelorarbeit, in Bearbeitung.
     
  • Nutzen der AAS für den Informationsaustausch im Engineering automatisierter Anlagen
    Viktor Vasilenko, Masterarbeit, in Bearbeitung.
     
  • Systematische Validierung und Implementierung eines Simulators, basierend auf FMI und SSP
    Duc Long Chu, Bachelorarbeit, in Bearbeitung.