A CPPS-architecture and workflow for bringing agent-based technologies as a form of artificial intelligence into practice-Reference-Cited by-同舟云学术

A CPPS-architecture and workflow for bringing agent-based technologies as a form of artificial intelligence into practice

Published:2022-06-01 Issue:6 Volume:70 Page:580-598
ISSN:2196-677X
Container-title:at - Automatisierungstechnik
language:en
Short-container-title:

Author:

Cruz Salazar Luis Alberto¹^ORCID,Vogel-Heuser Birgit²^ORCID

Affiliation:

1. Institute of Automation and Information Systems, Department of Mechanical Engineering, TUM School of Engineering and Design , 9184 Technical University of Munich , Munich , Germany

2. Institute of Automation and Information Systems, Department of Mechanical Engineering, TUM School of Engineering and Design, Core Member of MDSI and Member of MIRMI , 9184 Technical University of Munich , Munich , Germany

Abstract

Abstract Due to the increase in Artificial Intelligence in the production systems domain, Industry 4.0 (I4.0) experts must collaborate with autonomous systems. Industrial AI raises several concerns about existing standards, which provide guidelines and design patterns. One way to realize I4.0 systems are Industrial Agents (IAs) due to their inherent autonomy and collaboration. Multi-Agent Systems (MASs) are well suited for realizing distributed AI in I4.0 components. Considering the properties of IAs and existing standards, an MAS architecture is presented for flexible and intelligent Cyber-Physical Production Systems. The article compares I4.0 standardization efforts relevant to adapt AI in the form of IAs, illustrates how IA design patterns can be used, and introduces the Multi-Agent aRchitecture for Industrial Automation applying desigN patterNs practicEs “MARIANNE”. An implementation guideline is presented to put this CPPS into practice.

Funder

Bayerische Staatsministerium für Wirtschaft, Landesentwicklung und Energie

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

https://www.degruyter.com/document/doi/10.1515/auto-2022-0008/pdf

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