Examining the adoption of knowledge graphs in the manufacturing industry: A comprehensive review

Jorge Martinez-Gil*, Thomas Hoch, Mario Pichler, Bernhard Heinzl, Bernhard Moser, Kabul Kurniawan, Elmar Kiesling, Franz Krause

*Corresponding author for this work

Publication: Chapter in book/Conference proceedingChapter in edited volume

Abstract

The integration of Knowledge Graphs (KGs) in the manufacturing industry can significantly enhance the efficiency and flexibility of production lines and improve product quality. By integrating and contextualizing information about devices, equipment, production resources, location, usage, and related data, KGs can be a powerful operational tool. Moreover, KGs can contribute to the intelligence of manufacturing processes by providing insights into the complex and competitive manufacturing landscape. This research work presents a comprehensive analysis of the current trends utilizing KG in the manufacturing sector. We provide an overview of the state of the art in KG applications in manufacturing and highlight the critical issues that need to be addressed to enable a successful implementation. Our research aims to contribute to advancing KG technology in manufacturing and realizing its full potential to enhance manufacturing operations and competitiveness.

Original languageEnglish
Title of host publicationArtificial Intelligence in Manufacturing
Subtitle of host publicationEnabling Intelligent, Flexible and Cost-Effective Production Through AI
Place of PublicationCham
PublisherSpringer
Pages55-70
Number of pages16
ISBN (Electronic)9783031464522
ISBN (Print)9783031464515
DOIs
Publication statusPublished - 8 Feb 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024. All rights reserved.

Keywords

  • Cyber-Physical systems
  • Industry 5.0
  • Knowledge graphs
  • Manufacturing industry
  • Predictive analytics
  • Semantic modeling

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